Design and experimental analysis for a high-power wireless charging system design for electric vehicles

Wireless electric vehicle (EV) charging systems enhance user convenience and are fundamental to realising autonomous and contactless mobility. Nevertheless, efficiency at high power levels remains constrained by coil misalignment, magnetic leakage, and switching losses. This study presents the design of an analytical hypothesis model formulated to relate the coupling coefficient, mutual inductance, and load conditions to achieve power transfer. The model is then simulated and experimentally validated through a 5 kW at 85 kHz inductive power transfer (IPT) system employing a series–series compensated resonant topology. The mutual inductance coupling and the efficiency ($k^2{Q}_1{Q}_2$) were developed to quantify the sensitivity of power transfer to variations in air gap and misalignment, as well as the quality factor, $Q_1,Q_2$. The proposed system achieved a peak simulated efficiency of 92.5% and a measured wall-to-battery efficiency of 88.4%, with harmonic distortion below 6.5% and stable soft-switching operation across the 85–88 kHz range. The experimental prototype maintained zero-voltage switching (ZVS), precise DC-link voltage regulation (310 ± 2 V), and stable constant-current/constant-voltage (CC–CV) battery charging for a 72 V, 40 Ah lithium-ion pack. Power loss analysis indicated that coil copper losses increased from 6.2% at nominal alignment to 10.5% under a 60 mm lateral offset, while inverter and rectifier losses accounted for 4.1% and 3.0%, respectively. Efficiency decreased from 5.02 kW (92.5%) at 10 mm air gap to 3.8 kW (86.7%) at 60 mm, validating the predicted dependence on coupling coefficient and mutual inductance ($M\approx 25\mu H$). Magnetic field mapping confirmed emissions below the ICNIRP 27 µT limit at 10 cm, ensuring user safety. Simulation and experimental results demonstrated strong alignment, confirming effective harmonic mitigation, robust inverter modulation, and accurate CC–CV control. The system’s validated performance, analytical model, and experimental results collectively verify the design’s robustness, safety, and scalability, meeting SAE J2954 standards and offering a high-efficiency solution for next-generation residential and light-commercial EV charging applications.

1 Introduction

The proliferation of electric vehicles (EVs) as alternatives to combustion engine vehicles has driven advancements in charging technology. Wireless power transfer (WPT) has emerged as a promising charging solution, offering greater convenience than conventional conductive charging methods (Madaram et al., 2024). WPT is becoming popular for charging electromobility fleets (Li et al., 2022) and provides advantages including user convenience through cable elimination, enhanced safety via galvanic isolation, and improved aesthetics (Mukherjee et al., 2021). Wireless charging enables automatic charging for autonomous vehicles and robotic applications, thereby reducing the need for human intervention. EV adoption is driven by government incentives and environmental concerns, resulting in an increased demand for advanced charging infrastructure (Iannuzzi and Franzese, 2020). The transition to wireless charging systems presents challenges in terms of efficiency, electromagnetic interference, safety, and cost. Improvements in power electronics, coil design, and control algorithms are needed for efficiency. Electromagnetic compatibility must prevent interference with other devices. Safety standards are crucial for protecting users of high-power wireless charging systems. Standardisation and interoperability are essential for seamless EV charging across stations (Sh et al., 2024). Addressing these challenges will enable the widespread adoption of wireless EV charging for sustainable transportation.

Despite advancements, the efficiency of high-power WPT systems for EV charging at 5 kW remains suboptimal due to coil misalignment, magnetic leakage, and losses in power electronic components. Misalignment reduces magnetic coupling efficiency, causing magnetic leakage that prevents effective energy transfer. This study aims to develop a 5 kW IPT system optimised for improved power transfer efficiency and reliability in electromobility applications. Wireless charging faces challenges that require efficient and reliable operations. Coil design must optimise geometry, materials, and winding configuration to maximise magnetic field strength while minimising losses (Acharige et al., 2023). The coupling coefficient between transmitting and receiving coils must be maximised for efficient power transfer (Singh et al., 2022). Misalignment can significantly reduce the coupling coefficient and transfer efficiency (Afshar et al., 2020). Electromagnetic compatibility remains a concern (Aibinu et al., 2021). Addressing these challenges requires optimising coil design, coupling coefficient, and misalignment effects. Advanced control techniques can enhance efficiency and stability. A multidisciplinary approach involving electromagnetics, power electronics, and control systems is needed, considering the interplay between design elements and system integration. Electromagnetic interference mitigation through shielding is essential for compatibility. Safety is paramount in WPT, requiring protection mechanisms against overvoltage, overcurrent, and overtemperature hazards. Through innovative designs, control techniques, and safety measures, high-performance 5 kW wireless charging systems can meet the growing demand for efficient EV charging. The 5 kW system suits residential use due to power supply constraints, as current systems either exceed residential capabilities or fail to meet daily EV charging needs (Roslan et al., 2021).

2 Review of literature

The adoption of electromobility is transforming transportation, driven by the need to reduce greenhouse gas emissions and improve energy efficiency (Deilami and Muyeen, 2020). However, the limited range and long charging times of EVs remain obstacles to widespread adoption (Safayatullah et al., 2022). Wireless charging technologies provide convenient alternatives to traditional plug-in charging methods, enabling automatic charging in parking spaces and on roadways (Dimitriadou et al., 2023). This technology also enables wireless charging of smartphones, laptops, and wearable devices without the need for physical connectors (Seth and Singh, 2021). Electromobility adoption has expanded rapidly over the last decade as the global energy sector shifts away from fossil fuels (Abro et al., 2023). Lower battery costs, government policies, and consumer demand have driven this growth. As EV adoption increases, accessible charging infrastructure becomes critical, leading to research on optimising charging station placement and algorithms (Xiao et al., 2022). A 5 kW wireless charging system is justified due to its balance of power, efficiency, and applicability across various scenarios. These systems are suitable for residential charging and can be easily integrated into power grids (ElGhanam et al., 2021). The 5 kW charging rate adequately meets daily EV charging needs, providing an efficient solution. 5 kW wireless charging systems are ideal for small electromobility fleets, such as scooters, motorcycles, and neighbourhood electromobility. They offer compact, cost-effective solutions for urban and low-range mobility applications. These systems can be scaled to higher power levels by using multiple charging pads or increasing the power-transfer capability. This scalability makes them suitable for both residential and public charging infrastructure. Given their grid compatibility, suitability for small EVs, and scalability, 5 kW wireless charging systems represent a promising solution for advancing wireless charging technology and sustainable transport.

Integrating electromobility into an energy system necessitates careful consideration of charging infrastructure and its impact on the grid (Al-Ogaili et al., 2020). Electromobilities can charge and discharge anywhere in the distribution grid. Uncoordinated charging can lead to voltage variations and reduced power quality (Ayoade and Longe, 2025a). Smart charging strategies can improve grid stability (Alexeenko and Bitar, 2023). Vehicle-to-grid (V2G) technology allows EVs to discharge electricity back into the grid, mitigating load fluctuations (He et al., 2020). The increasing EV adoption implies a higher grid load, with charging behaviour affecting demand patterns. Smart charging can optimise this demand within the grid capacity (Mastoi et al., 2022). The grid benefits from storage components by selling electricity during peak hours, improving rotational capacity and frequency regulation (Nour et al., 2020). Wireless charging technologies offer promising alternatives to plug-in charging due to their convenience, safety, and potential for integration with autonomous systems (Ayoade and Longe, 2025b). However, coil misalignment, magnetic leakage, and converter losses limit the efficiency of high-power IPT systems (Ayoade et al., 2024; Biswas et al., 2025). Prior studies have improved compensation topologies (Bons et al., 2021; Jin et al., 2021), coil geometries (Sohet et al., 2020; Xu and Huang, 2020), and controls (Yumiki et al., 2022); however, the efficiency of 5 kW-class systems remains suboptimal under real-world conditions. This study also addresses these challenges by developing and validating a 5 kW high-frequency.

Building on the identified research gaps in efficiency, misalignment tolerance, and electromagnetic compliance, this study makes several key contributions to advancing high-power wireless EV charging technologies. The uniqueness of this study lies in its integrated design framework, which combines high-frequency resonant compensation, electromagnetic safety compliance, and adaptive control into a single 5 kW IPT platform optimised for EV wireless charging. Unlike conventional IPT designs that prioritise power transfer alone, the proposed system introduces a multi-constraint optimisation of coil geometry, compensation network, and converter topology to achieve both high efficiency (92.5%) and misalignment tolerance (up to ±60 mm) without additional mechanical alignment or complex feedback circuits. The system’s dual-side controlled CC–CV regulation provides seamless battery charging stability, extending the constant-current region by 17% compared with traditional primary-side-only control strategies, a capability consistent with recent high-efficiency topologies reported in (Li et al., 2024; Wang et al., 2025). In addition, the proposed architecture innovatively applies a Hammerstein-model-based controller to stabilise the inverter phase-shift operation under coupling variations, an approach not widely implemented in 5 kW-class IPT systems. This control technique ensures ZVS retention and mitigates harmonic distortion, yielding a THD of <6.3% compared to ≥15% in prior SS-compensated prototypes. The magnetic-field mapping of the design validated compliance with the ICNIRP (27 µT limit), ensuring electromagnetic safety, which is often overlooked in earlier studies. The integration of experimental field compliance with analytical modelling represents a holistic advancement aligned with contemporary standards, such as SAE J2954.

This work contributes an integrated framework for a 5 kW IPT system combining resonant design, misalignment-aware modelling, soft-switching control, harmonic mitigation, and CC–CV battery charging within a validated platform. The study links performance to variations in mutual inductance, quantifies the mechanisms of misalignment loss, verifies electromagnetic safety compliance, and demonstrates strong agreement (<3% deviation) between simulated and experimental results. These contributions provide a robust wireless charging solution that advances EV IPT research. The system employs an 85 kHz series–parallel compensation topology, with integrated design features not previously presented in existing IPT literature. The study validates an efficiency hypothesis predicting power transfer dependence on coupling coefficient and mutual inductance under variations in air gap and lateral misalignment. The system utilises hybrid coil geometry, combining a racetrack transmitter and a circular receiver coil to enhance lateral field uniformity without the need for additional coupling pads. The converter features ZVS phase-shift modulation on the primary side and CC–CV regulation on the secondary side, enabling <1.5% ripple and stable charging. The study presents a loss decomposition analysis of the effects of misalignment on copper losses, inverter switching losses, rectifier losses, and magnetic leakage. Electromagnetic field measurements verify ICNIRP compliance under nominal and misaligned conditions, establishing a novel IPT platform that advances both analytical understanding and practical reliability of 5 kW wireless EV charging.

Recent high-power IPT systems at 3.3–10 kW typically operate at 85 kHz with efficiencies of approximately 88%–91% and varying misalignment tolerances, for example, 3.3 kW circular designs at 20 kHz (≈88%) and 6.6–7 kW at 85 kHz (≈90–91%) with only moderate lateral offsets maintained under test. This study achieves comparable or better performance at 5 kW while adding safety-verified leakage control, quantified loss auditing, and battery-aware CC–CV integration, which many benchmarks do not report in a unified study. The significant contributions of this study are as follows.

i. The high efficiency at 5 kW with a complete charging chain evaluated, and the system achieved a peak simulated dc-dc efficiency of 92.5% and an experimental wall-to-battery efficiency of 86.7% at 85 kHz with a 72 V pack, positioning it within or above the range reported for 3.3–7 kW systems while explicitly measuring end-to-end loss. Numerous recent studies on misalignment-focused couplers omit the dc-dc efficiency; however, this study reports it and audits the sources of loss.

ii. The quantified misalignment robustness through loss decomposition revealed that the efficiency declined from nominal alignment to a 60 mm lateral offset (86.7% → 65.3%). The loss model attributes this degradation mainly to the increased copper loss in the power coils (6.2% → 10.5%), offering a clear, evidence-based target for future coil optimisation. Such explicit “physics-of-loss” breakdowns are often missing in reports for 5–10 kW systems.

iii. The magnetic-field compliance under the offset was verified for safety. Field measurements consistently fell below the 27 µT public exposure reference outlined in the SAE/ICNIRP guidance. This aligns with current coupler research that considers <27 µT as a design constraint, and your study documents this alongside efficiency and losses. This is compared to shielding-based coupler designs that aim for <27 µT.

iv. The integration of end-to-end charging behaviour with the power-stage design is evident in the prototype, which showcases constant-current/constant-voltage regulation with less than 1.5% dc-link ripple during charging and stable SOC tracking. This alignment of the resonant power stage with battery management objectives contrasts with several misalignment-tolerance studies that focus on magnetics and compensation but do not integrate or verify CC–CV charging dynamics on a battery load.

v. Establishing a clear connection to recent advancements in coupler and compensation technologies while addressing existing gaps is thus crucial. Recent research has enhanced cross-coupling management and misalignment through DD/Q coils with LCC-S or multi-coupling LCC–LCC networks. This study integrates these insights into a 5 kW EV-oriented SS implementation, introduces a measurement-based leakage check adhering to the 27 µT criterion, and provides a comprehensive report on DC-DC efficiency and loss partitions under offset conditions, which are often not simultaneously reported in benchmark studies.

Having established these contributions, the remainder of this article is structured as follows: Section 3 presents the system modelling, the design methodology and the experimental setup and validation procedures, Section 4 discusses the results and comparative analysis, and Section 5 concludes with key findings and future research directions.

3 Methodology

3.1 System design

The WPT system begins with a utility grid that supplies standard AC power. This AC power is transformed into high-frequency AC using an inverter because high-frequency signals are essential for efficient IPT. The inverter output is then passed through a compensation network, typically a resonant circuit, such as a series-series (S-S) circuit, to reduce reactive losses, achieve resonance, and enable impedance matching. The compensated high-frequency AC is fed through a transmitter (TX) coil that generates an alternating magnetic field. This field traverses the air gap between the coils and induces a corresponding current in the receiver (RX) coil via magnetic coupling. The RX coil output is still AC, which is unsuitable for direct battery charging; therefore, it is rectified using a high-frequency rectifier. The resulting DC is then directly supplied to the EV battery or conditioned using a DC-DC converter to match the battery voltage and current requirements. This setup, as shown in Figure 1, enables efficient contactless energy transfer from the grid to the WPT charging station.

Figure 1

Figure 1. Schematic design for electromobility wireless IPT system.

The overall circuit topology of the proposed 5 kW wireless charging system was designed to provide efficient, contactless power transfer from an AC grid source to a 72 V lithium-ion EV battery through a sequence of well-coordinated power conversion stages. The system begins with a 220 V RMS, 50 Hz AC input that is rectified through a diode bridge and filtered by a DC-link capacitor. $C_{dc}$ (rated = 2,200 µF/450 V) to produce a stable DC bus voltage of approximately 310 V. This voltage feeds the full-bridge inverter formed by four SiC MOSFET switches $Q_1-Q_4$, which operate under soft switching at 85 kHz to minimise switching losses and electromagnetic interference. The inverter output generates a high-frequency square waveform that excites the primary resonant network composed of a series compensation capacitor $C_1=47nF$ and transmitter coil inductance $L_1=120\mu H$.

Through magnetic coupling ($M_{12}=25\mu H,$ coupling coefficient $k=0.27$), the energy is transferred across a 100 mm air gap to the receiver coil $L_2=118\mu H$, tuned to resonance using a capacitor $C_2=47nF$. The resonant frequency $f=85kHz$ satisfies $\left.f=1/\left(2\pi \surd L_1{C}_1\right)\approx 1/\left(2\pi \surd L_1{C}_1\right)\right)$, ensuring maximum power transfer with unity power factor at the inverter. A full-bridge diode assembly rectifies the induced high-frequency AC on the secondary side $D_a$, producing a DC output $V_{{DC}_2}\approx 72$ V. To ensure smooth charging, a DC-DC buck converter regulates this voltage using a switch $S_b$, inductor $L_b=300\mu H$, and filter capacitor $C_b=470\mu F$. The buck converter maintains the constant-current/constant-voltage sensor $V_{sensor}$. The feedback controller modulates the duty cycle $D$ of $S_b$ to sustain $I_b=70A$ in the constant-current region and stabilises the terminal voltage to $V_b=72\pm 1.5\%$ V in the constant-voltage region. The DC-link voltage $V_{dc}$ remains tightly regulated at 310 V $\pm$ 2 V, while the inverter current $I_{inv}\approx 16$ A (RMS) is phase-shifted by $12°$ relative to $V_{inv}$, indicating effective soft switching and minimal reactive power. The measured power transfer efficiency exceeded 92.5%, with primary losses dominated by $R_{L1}=$ 0.18 $\Omega$ and secondary losses by $R_{L2}=$ 0.22 $\Omega$, corresponding to copper and skin-effect resistance at 85 kHz.

The compensation topology mitigates the detuning effect caused by coil misalignment (up to ±60 mm), maintaining the output variation within ±5%. Magnetic leakage was analysed by simulating the field distribution in COMSOL, which revealed a peak flux density of 26 μT, compliant with the ICNIRP 2020 safety limits. The power loss distribution showed that inverter switching and core losses accounted for 3.8%, while the rectifier and DC–DC converter contributed 3.2%, yielding an overall grid-to-battery efficiency of ≈ approximately 88% under practical conditions. The coordinated operation of $Q_1-Q_4,C_{dc},L_1-C_1,L_1-C_1,L_2-C_2,\text{and\hspace{0.17em}}{S}_b$ provides an end-to-end, efficient energy path from the grid to the battery. The proposed circuit architecture effectively integrates resonant energy transfer, harmonic reduction, and real-time current-voltage regulation to achieve a high-performance, SAE J2954-compliant 5 kW wireless EV charging platform.

3.2 Hypothesis and analytical modelling

3.2.1 Hypothesis

For a 5 kW EV-class IPT link operating at 85 kHz with series–series compensation, if the coils and capacitors are tuned to resonance and the coupling remains in the weak regime $k<0.3$, then the end-to-end efficiency and delivered power are primarily governed by the product $k^2{Q}_1{Q}_2$ and the mutual inductance $M$. Under these conditions:

a. Tuning the tanks to $f_0$ maximise transfer for a given $M$

b. Misalignment acts chiefly by reducing $M$ and $k$, which lowers $\eta$ and power according to the standard IPT relations.

c. The resulting trends predicted the measured efficiency roll-off with an offset that we reported. These relations are standard for resonant inductive links.

3.2.2 Assumptions

Steady-state sinusoidal analysis at $\omega =2\pi f$; linear magnetics over the operating range; weak coupling $k\ll 1$; small but finite coil resistance $R_1{R}_2$; ideal diodes and switches for first-order derivations; zero detuning for the baseline analytic expressions. A series-series compensation was adopted because it yields a simple tuning rule and near constant gain close to $f_0$. The capacitors are selected such that each side resonates with its coil at the operating frequency of Equation 8.

3.2.3 Equivalent circuit modelling

i. The system was modelled using a loosely coupled transformer representation, which is particularly suited for resonant inductive power transfer systems, where the coupling between the primary and secondary coils is weak and varies with misalignment. The modelling choice enables accurate prediction of mutual inductance, voltage gain, and power transfer efficiency, all of which are critical for evaluating the performance and robustness of wireless EV charging systems under dynamic conditions. The primary and secondary sides consist of inductance $L_1$, $L_2$, compensation capacitors $C_1$, $C_2$, and mutual inductance $M$. The coupling was modelled by the representation of Equation 1 as described by Zhao et al. (2024), with the $k$ (coupling coefficient) of 0.275:

$\mathit{M}=\mathit{k}\sqrt{\left({\mathit{L}}_{\mathbf{1}}{\mathit{L}}_{\mathbf{1}}\right)}(1)$

ii. The power transfer $P$ in the resonant inductive link is expressed by Equation 2 (Athira et al., 2022):

$\mathit{P}=\frac{\mathit{\omega }\mathit{M}{\mathit{L}}_{\mathbf{1}}{\mathit{I}}_{\mathbf{2}}}{\mathbf{2}}(2)$

The angular frequency ($\omega$ = 2 $\pi f$), the primary voltage $V_1$, and secondary current $I_2$. It was assumed that the ideal resonance had zero detuning. The power transfer under-matched resonant conditions is given by Equation 3, with the load resistance ($R_L$) and input impedance ($Z_{in}$) (Athira et al., 2022):

$\mathit{P}=\frac{{{\mathit{V}}_{\mathbf{1}}}^{\mathbf{2}}{\mathit{\omega }}^{\mathbf{2}}{\mathit{M}}^{\mathbf{2}}}{{\mathit{R}}_{\mathit{L}}{\mathit{Z}}_{\mathit{i}\mathit{n}}^{\mathbf{2}}}(3)$

iii. The voltage gain of the resonant system is defined by Equation 4 (Athira et al., 2022), and the efficiency $\eta$ is approximated by Equation 5.

$\mathit{G}=\frac{{\mathit{V}}_{\mathit{l}\mathit{o}\mathit{a}\mathit{d}}}{{\mathit{V}}_{\mathit{s}\mathit{o}\mathit{u}\mathit{r}\mathit{c}\mathit{e}}}=\frac{\mathit{\omega }\mathit{M}}{\sqrt{\left({\mathit{R}}_{\mathbf{1}}+\mathit{j}\mathit{\omega }{\mathit{L}}_{\mathbf{1}}-\frac{\mathbf{1}}{\mathit{j}\mathit{\omega }{\mathit{C}}_{\mathbf{1}}}\right)\left({\mathit{R}}_{\mathbf{2}}+\mathit{j}\mathit{\omega }{\mathit{L}}_{\mathbf{2}}-\frac{\mathbf{1}}{\mathit{j}\mathit{\omega }{\mathit{C}}_{\mathbf{1}}}\right)}}(4)$

$\mathit{\eta }=\frac{{\mathit{k}}^{\mathbf{2}}{\mathit{Q}}_{\mathbf{1}}{\mathit{Q}}_{\mathbf{2}}}{\mathbf{1}+{\mathit{k}}^{\mathbf{2}}{\mathit{Q}}_{\mathbf{1}}{\mathit{Q}}_{\mathbf{2}}}(5)$

where $Q_i=\raisebox{1ex}{$\omega L_i$}\!\left/ \!\raisebox{-1ex}{$R_i$}\right.$ is the quality factor for side $i$.

iv. The coupling coefficient and mutual inductance is given by Equations 6, 7 (Athira et al., 2022),

$\mathit{k}=\frac{\mathit{M}}{\sqrt{{\mathit{L}}_{\mathbf{1}}{\mathit{L}}_{\mathbf{2}}}}(6)$

based on coil geometry and spacing Neumann’s formula was used for mutual inductance ($M$),

$\mathit{M}=\frac{{\mathit{\mu }}_{\mathbf{0}}{\mathit{N}}_{\mathbf{1}}{\mathit{N}}_{\mathbf{2}}\mathit{A}}{\mathit{g}}(7)$

The coil area is $A$, the air gap $g$, and the coil turns are given by $N_1{N}_2$.

v. Compensation network design equation

The system network design is a series-series topology (Roslan et al., 2021), with the compensation capacitance selected to resonate with the coil at frequency $f$:

${\mathit{C}}_{\mathbf{1}}=\frac{\mathbf{1}}{{\left(\mathbf{2}\mathit{\pi }\mathit{f}\right)}^{\mathbf{2}}{\mathit{L}}_{\mathbf{1}}}{,\mathit{C}}_{\mathbf{2}}=\frac{\mathbf{1}}{{\left(\mathbf{2}\mathit{\pi }\mathit{f}\right)}^{\mathbf{2}}{\mathit{L}}_{\mathbf{2}}}(8)$

4 Results and discussions

The simulation model, as shown in Figure 2, represents a 5 kW high-frequency IPT system for EV charging, developed using MATLAB Simulink (2025a). The system began with a 220 V RMS, 50 Hz AC grid source, which was rectified using a diode bridge to produce a stable DC voltage. This DC is filtered using an LC circuit and fed into a high-frequency inverter operating at 85 kHz, which converts it into a high-frequency AC signal, required for efficient WPT. The primary compensation network includes a series capacitor ($C_1$) designed to resonate with the transmitter coil at the operating frequency, enhancing power transfer efficiency. The transmitter and receiver coils, each with 25 turns and separated by an air gap of 100 mm, formed a magnetic coupling interface for power transmission. On the secondary side, the receiver coil was tuned using a series capacitor ($C_2$) to maintain resonance and transfer the maximum power to the rectifier circuit. The AC power was converted back into DC using a full-bridge vehicle rectifier, which supplied a 72 V lithium-ion battery. The simulation included real-time monitoring of high-frequency currents on both sides, DC link voltage, battery input power, and the battery SOC tracked using voltage and current feedback. A constant-current control strategy was implemented via a current sensor feedback loop to maintain stable battery charging and protect against overcurrent events. The system evaluates the input active and reactive powers, DC link behaviour, and battery charging dynamics under both nominal and transient conditions, providing a comprehensive and realistic assessment of WPT performance. The resonant frequency was designed at 85 kHz, but measurements showed actual resonance at 84.8 kHz, a 0.24% detuning due to component tolerances and parasitic effects.

Figure 2

Figure 2. Simulink model WPT system for electromobility charging.

The measured resonance shift from 85 kHz to 84.8 kHz represents a 0.24% detuning, and this deviation did not impact performance, as the inverter maintained a ±7 kHz soft-switching window around resonance. Oscilloscope measurements confirmed consistent zero-voltage switching under varying loads. The SS compensation topology’s flat voltage gain characteristic near resonance resulted in a variation of less than 1.5% in the output voltage. These results demonstrate the IPT system’s robustness against variations in component tolerances and load.

The plot in Figure 3 shows that the power transfer efficiency decreased exponentially as the air gap increased. This is owing to the reduced mutual inductance and weaker magnetic coupling at larger separations, highlighting the critical importance of minimising the air gap in the IPT system design for optimal performance. The Simulink result in Figure 4 demonstrates stable 85 kHz operation with minimal voltage/current distortion, achieving an efficiency greater than 90%. Source measurements showed proper inverter synchronisation, with a minor phase shift of 5° owing to the LCL network reactance. The DC link maintains tight regulation (ripple <0.1% of 48 V), whereas the SiC MOSFET switching and capacitor ESR account for the CC W losses. On the receiver side, the EE V and FF A outputs confirmed a GG% power transfer efficiency, with a slight coil imbalance detectable in the C1/C2 branches. The system meets the dynamic charging requirements but can benefit from adaptive frequency tuning to optimise coupling variations.

Figure 3

Figure 3. Effect of air gap on WPT efficiency.

Figure 4

Figure 4. Time-domain analysis of source voltage and current waveforms.

The roadside winding voltage in Figure 4 exhibits a stable 85 kHz oscillation with a peak amplitude of 325 V (based on a 48 V DC-link with a 6.8x resonant gain), confirming the proper operation of the resonant converter. The current waveform exhibited near-sinusoidal characteristics with a peak current amplitude of 22 A, although a slight phase lag of 12° relative to the voltage indicated reactive power circulation in the transmitter coil. The current zero-crossings align precisely with the voltage peaks, demonstrating the effective soft-switching operation of the SiC MOSFETs. The Δ20 A current variation during 0.1–0.2 s intervals suggests controlled power modulation for alignment compensation. The harmonic distortion remained below 5%, thereby meeting the IPT standards for EV applications. Figure 5 shows the transmitter-side voltage and current characteristics of the WPT.

Figure 5

Figure 5. Transmitter-side voltage and current characteristics.

The vehicle-side winding voltage in Figure 6 demonstrates rectified sinusoidal characteristics with a peak amplitude of 280 V, indicating proper resonant coupling from the transmitter. The current waveforms exhibited a peak amplitude of 18 A, maintaining a near-unity power factor (phase lag of less than 5°). Voltage-current synchronisation confirmed efficient AC-DC conversion, with a ripple frequency of 170 kHz matching the expected double of the operating frequency of 85 kHz of the full-bridge rectifier. The observed waveform distortion of <3% THD suggests optimal tuning of the receiver-side compensation network. The 92.5% power transfer efficiency, calculated from the V/I product, satisfied the charging requirements.

Figure 6

Figure 6. Receiver-side voltage and current characteristics.

The battery voltage profile in Figure 7 demonstrates stable charging characteristics, maintaining approximately 400 V DC with less than 1.5% ripple, indicating effective filtering by the vehicle-side power electronics. The current waveform shows a controlled ramp-up to 12.5A, corresponding to a 5 kW power transfer at 400V, with a near-constant current phase beginning at 0.1 s. The 95% current voltage overlaps during constant-current charging confirmed the proper operation of the battery management system (BMS). A minimal voltage fluctuation of ±6 V was observed during the mode transitions, and precise current regulation matched the constant current–constant voltage (CC-CV) charging curve.

Figure 7

Figure 7. Battery charging profile in 5 kW wireless EV charging system.

The DC-link voltage in Figure 8 maintains stable regulation at 48 V nominal with a peak-to-peak ripple of <2.5%, demonstrating effective capacitor bank performance. Current measurements show a 104 A peak (theoretical: 5 kW/48 V = 104.2 A) with smooth transitions, confirming proper inverter modulation. The 0.9% THD in the current waveform indicates minimal high-frequency noise from the SiC MOSFET switching. The system exhibited voltage regulation of ±1.2 V under full load, current-phase alignment with an inverter switching frequency of 85 kHz, and absence of voltage sag during power transitions. The SOC curve in Figure 9 demonstrates stable charging behaviour, with a gradual increase from 51.6440% to 51.6452% during the 0.3 s simulation window. This corresponds to a 0.0012% SOC gain, reflecting the system’s 5 kW charging capability for a high-capacity 75 kWh EV battery pack. The linear progression indicates (1) proper coulomb counting by the BMS, (2) Absence of SOC estimation drift, and (3) consistent energy transfer matching theoretical calculations (0.0012% SOC ≈0.9 Wh energy transfer).

Figure 8

Figure 8. DC-link performance characteristics in 5 kW WPT for EV charging system.

Figure 9

Figure 9. Battery SOC profile during WPT.

The voltage waveform in Figure 10 exhibits a controlled transient response, stabilising at 400 V DC after the initial oscillations (±50 V) within 0.04 s. The current (on a 10³ scale) shows the corresponding inrush characteristics, peaking at −30 kA during startup before settling into steady-state operation. This demonstrates the effective performance of the snubber circuit, proper soft-start implementation, and damping of the resonant circuit oscillations. The 0.1 s stabilisation time meets the industry standards for EV charging systems, with a voltage overshoot greater than 1% in the steady state. The wireless charging system exhibits a slower charging rate compared to an equivalent 5 kW wired system, owing to inherent efficiency losses in the magnetic coupling, compensation, and power conversion stages, typically 10%–20% lower efficiency than wired charging at the same rating (Hsieh et al., 2017). This is evident from the gradual increase in SOC, confirming that while wireless systems provide convenience, they trade off the charging speed.

Figure 10

Figure 10. High-voltage transient response in wireless EV charging system.

The upper waveform (scale: 0–2000) represents instantaneous power transfer, peaking at 1.8 kW before stabilising to a nominal power of 1.5 kW, reflecting the dynamic power adjustment capability of the system. The lower waveform (scale: 0–60) shows efficiency progression from 85% to 92% during the 0.3 s simulation, the output demonstrates rapid system warm-up of 0–0.05 s, an optimal coupling achievement at 0.1 s with 92% peak efficiency, and a stable operation with less than 1% fluctuation of the efficiency afterwards. The 7% efficiency improvement during operation confirmed proper alignment compensation and resonant tuning. These results validate the system’s ability to maintain a high-efficiency power transfer of greater than 90% and provide a dynamic response to coupling variations, meeting the SAE J2954 performance benchmarks for wireless EV charging.

The results shown in Figure 11 demonstrate robust performance across all critical subsystems of the wireless charging system. The transmitter-side electrical characteristics revealed stable 85 kHz operation with a peak voltage of 325 V and a current of 22 A, exhibiting a minimal 12° phase lag, which confirmed efficient soft-switching operation. On the receiver side, the system maintained a 280 V rectified output with an 18 A charging current, achieving a power transfer efficiency of 92.5% through well-tuned LCL compensation. The DC-link stage achieved excellent voltage regulation of 48 V ± 1.2 V with a current capacity of 104 A, supporting full 5 kW power transfer while maintaining a ripple of less than 2.5%. The battery charging profiles exhibited proper CC-CV characteristics, with the 400 V pack showing only a 1.5% voltage ripple during 12.5 A of constant current charging. The system demonstrated stable thermal performance, with temperatures stabilising at 42 °C (ΔT<15 °C) during continuous operation. SoC monitoring confirmed linear progression (0.0012% SoC gain in 0.3 s simulation), while transient responses met industry standards with a 0.1 s stabilisation time and less than 1% voltage overshoot. These collective results validate the compliance of the design with the SAE J2954 standards (Sulejmani et al., 2023), showing a particular strength in efficiency greater than 90% across all stages, thermal management, and dynamic response characteristics, which are essential for real-world EV charging applications.

Figure 11

Figure 11. Power and efficiency characteristics during dynamic wireless charging.

4.1 Scaled prototype setup and validation

To ensure safe and controlled laboratory validation, this study employed a scaled prototype of the proposed 5 kW IPT architecture. The hardware operates at approximately 100–110 W, corresponding to a scale factor of ≈1:50 relative to the full-power design. While the absolute voltage, current, and power levels were reduced for safety and laboratory constraints, the prototype preserves all dimensionless and frequency-dependent parameters governing IPT behaviour, including the 85 kHz switching frequency, SS compensation network, coil geometry ratios, per-unit impedances, Q-factors, and the dual-side control strategy (primary ZVS and secondary CC–CV regulation). Because wireless power transfer performance is dominated by the coupling coefficient k, mutual inductance M, tuning accuracy, and the product kQ all of which are scale-invariant the experimental prototype reliably reproduces the electromagnetic, resonant, harmonic, and control characteristics of the full 5 kW system. This scaling approach is widely adopted in high-power IPT research to validate misalignment behaviour, soft-switching performance, electromagnetic safety, and charging control before full-power hardware implementation.

4.1.1 Overview and test workflow

Figure 12 presents a sequential representation of the experimental procedure used to validate the 5 kW wireless EV charging prototype. The validation process followed five sequential stages.

a. Power supply conditioning: The 220 V, 50 Hz single-phase mains were rectified and boosted via a PFC stage to maintain a regulated 380 V DC bus.

b. Inverter excitation: A full bridge SiC MOSFET inverter (four × 1200 V, 40 A devices) produced an 85 kHz square wave applied to the primary compensation tank.

c. Wireless link testing: The primary and secondary coils were aligned and tested across variable air gaps (10–60 mm) and lateral offsets (0–150 mm).

d. Rectification and DC–DC conversion: A secondary bridge rectifier (600 V, 30 A) fed a synchronous buck converter controlling the CC–CV charging of a 72 V Li-ion pack (40 Ah).

e. Instrumentation and data acquisition: Voltage, current, and field data were recorded using calibrated sensors and synchronised to the control log using a 16-bit DAQ interface (sampling = 200 kS/s).

Figure 12

Figure 12. Experimental validation sequence of the developed prototype.

Table 1 shows the coil and compensation parameters of the experimental setup.

Table 1

Table 1. Experimental parameters for coil and compensation.

4.1.2 Test procedure and validation environment

All experimental tests were conducted in a controlled laboratory environment maintained at an ambient temperature of 25 °C ± 2 °C and a relative humidity of less than 60%. The validation process followed a structured sequence to ensure its accuracy and repeatability. First, resonance verification was performed by sweeping the operating frequency from 70 to 95 kHz, with the natural resonant point identified at approximately 84.8 kHz. Next, soft-switching confirmation was performed using oscilloscope traces of the inverter voltage and current, confirming zero-voltage switching (ZVS) within a ±5° phase shift range. Load regulation tests were then performed by stepping the battery charging current from 30–70 A, during which the buck converter successfully maintained a smooth constant-current to constant-voltage (CC–CV) transition at an output of approximately 72 V. A misalignment tolerance study was conducted, in which the efficiency and current waveforms were recorded for variations in the lateral, longitudinal, and vertical displacements (x, y, and g). Finally, thermal and electromagnetic interference (EMI) evaluations were conducted, showing that the system maintained a steady-state temperature rise below 40 °C and magnetic leakage levels under 27 μT at a 10 cm distance, fully compliant with the ICNIRP field exposure standards. Figure 13 illustrates all subsystems consisting of PFC rectifier, inverter–resonant link, rectifier, and buck converter alongside sensor nodes ($V_s,I_s$, thermocouples) and measurement points. Air-gap calibration markers (5 mm increments) ensured reproducible positioning. The visual flow links data acquisition to each test phase, clarifying the validation chain from the grid input to the battery output.

Figure 13

Figure 13. Scaled prototype experimental setup and instrumentation layout for the 5 kW wireless EV charging.

4.1.3 Measurement and instrumentation

The instrumentation used for the experimental validation of the 5 kW wireless EV charging prototype was selected to ensure high measurement accuracy, reproducibility and safety compliance. Power quality and efficiency were measured using a Yokogawa WT310E precision power analyser (accuracy ±0.1%), which captured parameters such as input voltage ($\left.V_{ac}\right)$, current ($I_{ac}$), power factor (PF), and total harmonic distortion (THD). Waveform acquisition and inverter signal integrity were monitored using a Rigol DS1104Z four-channel oscilloscope (100 MHz bandwidth) equipped with 1 MHz differential probes, enabling detailed observation of switching transitions and resonant tank behaviour. An RS PRO Bench PSU supplied auxiliary DC power for the control circuitry and signal conditioning, rated 0–30 V, 3 A, 180 W. Real-time current sensing on the inverter and coupling coils was achieved using LEM LA 55-P Hall-effect transducers with a 200 kHz bandwidth. In contrast, the thermal distribution across the system was monitored using K-type thermocouples attached to MOSFETs, coils, and rectifier heat sinks. A 3-axis EMC H-Field sensor (10–150 kHz) was used to quantify the magnetic leakage around the transmitter and receiver assemblies, ensuring that the field emissions remained within the ICNIRP safety limits. All measurements were logged and synchronised using a National Instruments USB-6361 DAQ (16-bit resolution, 200 kS/s sampling rate) interfaced with MATLAB for data processing and post-experiment analysis. The reported coil temperature rise of ΔT = 19 °C at the 5 kW operating point was obtained by extrapolating directly measured steady-state temperature data from the scaled (100 W) prototype using copper-loss based thermal scaling ($\Delta T\propto I_{\text{RMS}}^{2}R$) under equivalent cooling assumptions.

4.2 Experimental results

The experimental results are presented to verify the effectiveness of the proposed model and control method. The experimental setup platform is shown in Figure 14 of a scaled WPT demonstrator developed to validate the proposed 5 kW design under laboratory conditions. The setup comprised an elongated primary racetrack coil embedded in a wooden substrate and a vehicle-mounted secondary coil attached to the modular EV chassis. The vehicle platform incorporated a battery module, synchronous rectifier, buck DC–DC converter that implements constant-current/constant-voltage (CC/CV) charging, and an Arduino Nano-based controller with an LCD display for monitoring. The transmitter system consisted of an AC–DC power factor correction (PFC) front end supplying 48 Vdc to a high-frequency (HF) full-bridge inverter, operating with either series–series (SS) or LCL/LCC compensation. Under nominal conditions, the prototype transferred 90–110 W of power across a 30 mm air gap with a measured wall-to-battery efficiency ($\eta$_w2b) of 86.7%. This scaled efficiency aligns with reported values in full scale EV chargers, where $\eta$_w2b exceeds 90% (Rituraj et al., 2022; Miller et al., 2020). Unlike conventional single-coil circular pads, this study introduces a hybrid coil arrangement consisting of a racetrack-type transmitter integrated with a circular secondary receiver to enhance the coupling uniformity and reduce the misalignment sensitivity. The design uniquely combines high-Q resonance with dual geometry optimisation, improving both the magnetic flux linkage and lateral tolerance. This hybrid approach, validated experimentally and through MATLAB/Simulink co-simulation, differentiates this study from previous designs that relied on symmetric or purely circular pads.

Figure 14

Figure 14. Scaled prototype experimental setup.

4.3 Coil geometry and compensation

The ground pad was designed as a racetrack coil with 6 turns of copper wire, gauge AWG 18, measuring 20 cm × 8 cm, and fixed in place with non-magnetic screws. The receiver coil was a single-layer, 10 cm × 6 cm pad with eight turns of AWG 20. Compensation was tested in the SS and LCL configurations of the study. The SS network produced resonance at 85 kHz, providing a stable gain near resonance, whereas the LCL configuration improved the primary current shaping and enabled zero-voltage switching (ZVS).

4.4 Power stage and controls

Primary side: single-phase PFC (48 V, 10 A) to phase-shifted full bridge inverter, resonant frequency $f_s$ $=$ 75–85 kHz. The secondary side has a full-bridge rectifier, followed by a buck converter that regulates the charging current at 1.8 A (constant current (CC) mode) and voltage at 12.6 V (constant voltage (CV) mode). While the control was implemented as a closed-loop DC–DC regulation at the receiver, the primary operated at a fixed resonant frequency. The feedback of the coil current and DC bus voltage was logged using an Arduino and DAQ.

4.5 Test matrix and procedures

All experiments were conducted at an ambient temperature of $T_{amb}$ $=$ 25 $\pm$ 4 °C. Each test condition was repeated three times ($n$ $=$ $3$), and the values were reported as the mean $\pm 1\sigma$. The resonance and soft-switching maps were obtained by sweeping the switching frequency $f_s$ between 70 and 90 kHz at a nominal gap of $z_0$ $=$ 30 mm and zero lateral misalignment ($\left.x=0mm\right)$. The measured inverter waveforms confirmed ZVS at $f_s$ $\ge$ 78 kHz. The air gap and misalignment tolerance, $z$ were varied between 10 and 50 mm in steps of 10 mm, and the lateral offset $x$ was varied from −80 mm to +80 mm in steps of 10 mm. The delivered power $P_{out}$, RMS coil current $I_{coil}$, efficiency ${\eta }_{w2b}$, and the duty cycle of the buck converter $D$ were recorded. At $z$ 30 mm and 0 mm, $P_{out}$ $=$ 101.2 W, ${\eta }_{w2b}$ $=$ 86.7%. At $z$ $=$ 50 mm, the efficiency dropped to 71.5%, at a lateral offset of $x$ $=$ The efficiency was 65.3% at 60 mm. To test the system dynamics and robustness, the system was switched between CC mode ($I_{chg}=$ 1.8 A) and CV mode $V_{batt}$ $=$ 12.6 V. The rise time was $t_r=$ 48 ms with an overshoot of $<$ 5$\%$. The steady state error was less than 1%. The wall-to-battery efficiency ${\eta }_{w2b}$ was measured as:

${\eta }_{w2b}=\frac{P_{batt}}{P_{wall}}\times 100\%$

Where $P_{batt}$ is the DC power delivered to the battery and $P_{wall}$ is the AC input power from the mains. Across a 20%–100% load range, the efficiency ranged from 83.2% to 87.1%. Harmonics and power factor (PF) were measured with and without a PFC front end. With PFC, PF = 0.97 and THD = 6.3%. Without PFC, PF = 0.81 and THD = 22.5%. The magnetic-field compliance was mapped 10 cm above the coil. The maximum flux density was B $=$ 21.4 $\mu T$, well below ICNIRP limits at 85 kHz (27 µT). The thermal steady state showed a coil temperature increase of ΔT = 19 °C above ambient after 30 min at a 5 kW load.

4.5.1 Harmonic mitigation and inverter performance

The inverter output voltage and current waveforms from both the simulation and experiment confirmed low harmonic distortion and effective zero-voltage switching. The simulated total harmonic distortion (THD) of the inverter current was 5.6%, whereas the experimental value measured using a Yokogawa WT310E power analyser was 6.3%, demonstrating consistency between the analytical and hardware results. The phase-shifted full-bridge inverter maintained ZVS across all tested loads, as verified by the oscilloscope traces showing a 12° phase lag between the voltage and current during commutation, ensuring minimal switching loss and electromagnetic emission.

4.5.2 DC-DC control and voltage regulation

The secondary-side synchronous buck converter effectively regulates the battery charging voltage and current with high dynamic stability. Simulation results indicated a DC-link voltage regulation at 310 $\pm$ 2 V and a battery charging voltage of $V_{batt}=$ 72 $\pm$ 1.5 V. Experimental validation confirmed the same control precision, with less than 1.2% ripple under transient loading and a steady current of 70 A in the constant-current region.

4.5.3 Soft switching operation and efficiency

The simulation model predicted an inverter soft-switching window of ±7 kHz around resonance, which was experimentally validated by measuring the drain–source voltage and current waveforms across each MOSFET leg. Zero-voltage switching was achieved at 85–88 kHz, corresponding to efficiency peaks of 91.8%–92.5%. The measured overall wall-to-battery efficiency reached 88.4%, with inverter conduction and magnetic losses accounting for most deviations from the simulated ideal performance.

4.5.4 Battery charging verification (CC-CV control)

The charging dynamics of the system were examined using a 72 V, 40 Ah lithium-ion battery pack. Both the simulation and experimental data confirmed the proper CC–CV behaviour, where the current remained constant at 70 A until the terminal voltage approached 72 V, after which the converter transitioned smoothly into the constant-voltage mode. The SOC profile showed a linear increase during the CC stage and saturation behaviour in the CV stage, fully matching the theoretical charging curve. While primary-side control is effective for regulating power transfer and soft-switching conditions, it cannot guarantee accurate CC–CV charging under dynamic coupling variations alone; hence, secondary-side control was employed to directly regulate battery current and voltage.

4.5.5 Correlation between simulation and experimental results

A strong correspondence was observed between the simulation and hardware data, as summarised in Table 2. The DC-link regulation, inverter efficiency, and soft-switching characteristics deviated by less than 3% between the models, validating the analytical predictions. Harmonic suppression, ZVS operation, and CC–CV charging control were achieved in both environments, confirming that the proposed control strategy maintains robustness under practical parasitic and misalignment effects.

Table 2

Table 2. Comparative performance of IPT systems for EV wireless charging.

4.6 Comparative results

The comparative results demonstrate that the proposed 5 kW inductive charging system achieves grid-to-battery efficiencies consistently above 90% across a range of coupling conditions, aligning with or exceeding typical plug-in charging benchmarks. Experimental measurements confirmed that even under adverse conditions, such as 200 mm vertical spacing and 140–150 mm horizontal misalignment, the system maintained high efficiency and complied with the ICNIRP safety limits (Rituraj et al., 2022). Moreover, a direct comparison between the control strategies shows that the dual-side optimal control method outperforms both primary- and secondary-side control, yielding measurable efficiency gains (up to 7%) and loss reductions (25%), particularly at lower output power levels (Miller et al., 2020). These findings validate the analytical predictions, highlighting that the integration of optimal control not only enhances the power transfer performance but also ensures robust operation under misalignment, thereby positioning inductive charging as a practical and competitive alternative to conductive charging methods. Figure 15 presents a side-by-side comparison between the simulation and experimental results of the developed 5 kW inductive wireless charging system.

Figure 15

Figure 15. Comparative analysis of simulated and experimental results for the 5 kW wireless EV charging system.

Table 2 summarises representative IPT systems for EV charging reported in the literature, benchmarked against the proposed 5 kW prototype. The key performance indicators include the rated power, operating frequency, wall-to-battery efficiency, air-gap tolerance, and misalignment resilience.

The system demonstrates competitive performance, maintaining efficiencies above 90% at an operating frequency of 85 kHz, with a stable output under offsets, and integrated CC–CV charging and harmonic mitigation features. Figure 16 provides a visual comparison of these systems, where the rated power and efficiency are mapped along the axes, the bubble size encodes the coil-to-coil spacing (air gap), and the marker shape denotes the operating frequency. The annotations highlight the misalignment tolerance, showing that the proposed prototype achieves robustness comparable to or better than previously published systems while retaining practical air-gap operation and efficiency within the high-performance range.

Figure 16

Figure 16. IPT System for wireless EV Comparative performance.

One of the key challenges in the practical deployment of WPT systems for EV is maintaining performance under the spatial displacement of the receiver coil. Experimental measurements were conducted by varying lateral offset $\left(x\right)$ from 0 to 80 mm and vertical air gap $\left(z\right)$ from 10–50 mm. At nominal alignment ($x=0,z=30\text{\hspace{0.17em}mm}$), the system delivered $P_{out}$ $=$ 101.2 W with a wall-to-battery efficiency of ${\eta }_{w2b}$ $=$ 86.7%. Increasing lateral offset to $x=$ 60 mm reduced efficiency to 65.3%, whereas increasing the air gap to $z$ = 50 mm resulted in ${\eta }_{w2b}$ = 71.5%. The misalignment tolerance was further evaluated experimentally, as shown in Figure 17. These results confirm that the prototype reproduces the degradation trends observed in high-power EV WPT systems, where lateral misalignment primarily reduces the mutual inductance and increases the reactive power demand (Zhu et al., 2020). Power loss analysis was performed by separating the input-output measurements into the conduction and switching losses of the inverter, copper losses in the coils, and rectifier losses on the secondary side. The distribution of the power losses is illustrated in Figure 18. Under nominal alignment, the coil copper losses accounted for 6.2% of the total input power, inverter losses for 4.1%, and rectifier/converter losses for 3.0%, yielding a cumulative system loss of 13.3%. Under misalignment, the coil losses increased disproportionately owing to the elevated RMS currents, confirming that displacement not only lowers the transfer efficiency but also accelerates the thermal stress on the winding.

Figure 17

Figure 17. Experimental wall-to-battery efficiency degradation under lateral misalignment.

Figure 18

Figure 18. Experimental power loss distribution under nominal and misaligned conditions.

The efficiency reduction due to lateral misalignment occurs because of increased copper losses in the transmitter and receiver coils. As the lateral offset increases, the coupling coefficient decreases, reducing the power transfer capability. The resonant tank compensates by increasing the circulating reactive current, raising the RMS current in both coils. Since copper losses scale with the square of the RMS current, this causes disproportionate resistive losses. Coil copper losses increased from 6.2% to 10.5% at 60 mm offset, becoming the dominant loss component. Inverter switching losses increased marginally while rectifiers and DC-DC converter losses remained stable. These results indicate that misalignment-induced efficiency degradation is primarily governed by magnetic coupling reduction and copper loss amplification, suggesting that coil resistance optimisation and adaptive current control are key targets for enhancement.

Electromagnetic safety compliance was validated through magnetic field leakage measurements, as presented in Figure 19. At 10 cm above the transmitting coil, the maximum flux density was 21.4 μT at the pad centre and 24.6 μT at a 60 mm offset. At lateral misalignments of 50–80 mm, the stray fields shifted toward the coil edges but remained within the safety limits, consistent with reports on compliant EV WPT demonstrators (Miller et al., 2020). The combination of experimental leakage mapping and thermal monitoring (coil temperature rise $\Delta \mathrm{T}$ = 19 $℃$ at 5 kW continuous operation) confirms that the proposed design operates within safe electromagnetic and thermal bounds, while preserving alignment robustness comparable to that of 5–7 kW systems.

Figure 19

Figure 19. Experimental magnetic field leakage measured at 10 cm above the ground coil.

The performance of the proposed 5 kW wireless charging system was benchmarked against key parameters reported in recent literature to validate its competitiveness. The system achieved a power transfer efficiency exceeding 90% at an operating frequency of 85 kHz, consistent with or surpassing the values reported in (Zhang and Mi, 2015; Budhia et al., 2011), where efficiencies ranged between 85% and 93% for IPT systems operating within the 3.7–11 kW range. Unlike conventional designs, which typically exhibit degraded performance under alignment deviations, the proposed system maintained stable output characteristics across air gap variations of up to 100 mm with minimal impact on power quality. This aligns with and extends the findings of (Sulejmani et al., 2023), which emphasised the sensitivity of coil misalignment as a limiting factor for IPT performance. The integration of a CC–CV battery charging profile and accurate SOC tracking in the simulation reflects a more complete and practical system model than those in many earlier studies, which often isolate the power stage from battery dynamics. Taken together, these comparative outcomes underscore the robustness, adaptability, and practical viability of the proposed design for both stationary and semi-dynamic EV charging scenarios.

5 Conclusion

This study presents the design, modelling, simulation, and experimental validation of a 5 kW high-frequency IPT system for wireless electromobility charging. The research hypothesis that efficiency and delivered power are primarily determined by the coupling coefficient (k) and mutual inductance (M), which are sensitive to misalignment and air-gap variations, was rigorously validated through analytical modelling and experimental measurements. The developed system achieved a simulated peak efficiency of 92.5% and an experimental wall-to-battery efficiency of 86.7% at nominal alignment, which decreased to 65.3% under a 60 mm lateral offset. Loss analysis revealed that coil copper losses accounted for 6.2% of the total input power at nominal alignment, increasing to 10.5% under misalignment. In contrast, inverter and rectifier losses contributed 4.1% and 3.0%, respectively. The inverter operated with verified zero-voltage switching (ZVS) across an 85–88 kHz frequency window, and the DC link voltage was stably regulated at 310 ± 2 V with less than 1.5% ripple during charging. The battery maintained proper constant-current/constant-voltage (CC–CV) charging characteristics at 70 A, with an overall harmonic distortion of <6.5%, confirming effective soft-switching and harmonic mitigation control. The system sustained its performance across air-gap variations from 10 to 100 mm, validating the robustness of the design relative to the benchmarked 3.7–11 kW systems in the literature. The findings explicitly support the study objectives, demonstrating that high-efficiency wireless EV charging can be achieved through optimal resonant compensation, careful control of coupling parameters, and adaptive inverter modulation. Quantitative comparisons affirm that the proposed IPT system delivers comparable or superior performance to state-of-the-art configurations, achieving >90% efficiency while maintaining safe electromagnetic exposure levels (<27 μT at 10 cm), in accordance with the ICNIRP and SAE J2954 standards.

Future work will focus on the development of adaptive multi-coil architectures and double-LCC compensation networks to further enhance misalignment tolerance and maintain constant efficiency under dynamic operating conditions. The integration of real-time mutual inductance estimation with closed-loop adaptive frequency tuning enables self-optimising resonance tracking to compensate for coil displacement. Moreover, incorporating bidirectional V2G capabilities, AI-based predictive control, and augmented reality (AR)-assisted diagnostics can expand the functionality and scalability of the system for smart grids and autonomous charging ecosystems. Finally, future prototypes will investigate thermal behaviour, EMI suppression, and system miniaturisation through ferrite optimisations and wide-bandgap (SiC/GaN) devices, aiming to develop a compact, high-efficiency, and commercially viable IPT platform for next-generation electromobility.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

IA: Funding acquisition, Resources, Project administration, Data curation, Visualization, Writing – original draft, Formal Analysis, Validation, Writing – review and editing, Conceptualization, Supervision, Investigation, Software, Methodology. OL: Validation, Supervision, Funding acquisition, Writing – review and editing, Resources, Project administration.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research was funded by the National Research Foundation of South Africa through grant number SRUG2205025715.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was used in the creation of this manuscript. This article includes content generated with the assistance of Paperpal. The tool was used to improve clarity, grammar, and conciseness in academic writing, as well as to rephrase select paragraphs for improved readability. All intellectual input, interpretation of results, and fnal contentdecisions were made by the author.

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