Research progress on Intelligentization and Electrification of Automobiles

The global automotive industry is undergoing a transformative paradigm shift, driven by the dual pillars of electrification and intelligentization. To achieve carbon neutrality and enhance transportation efficiency, electric vehicles (EVs) have emerged as the primary solution for future mobility. At the same time, the rapid evolution of artificial intelligence, high-speed connectivity, and advanced sensor technologies is propelling the industry toward high-level autonomous driving and interconnected ecosystems.

This Research Topic explores the synergistic integration of these two domains, the point at which advanced electric powertrains meet smart control algorithms to define the next generation of vehicles.

The challenge

Despite isolated advances in electric powertrains and autonomous driving, the deep integration of electrification and intelligentization presents formidable interdisciplinary challenges. The primary problem lies in overcoming the competing demands between power-intensive autonomous computing systems (e.g., LiDAR, AI inference) and the stringent energy efficiency required for extended EV range. Ensuring functional safety and real-time responsiveness across these complex, coupled dynamics remains a critical bottleneck.
Recent advances in Software-Defined Vehicles (SDVs), digital twins for Battery Management Systems (BMS), deep learning-based trajectory planning, and low-latency Vehicle-to-Everything (V2X) connectivity offer promising pathways to bridge this gap.

Goal and scope

The goal of this Research Topic is to address these integration bottlenecks by compiling state-of-the-art methodologies. Focusing on what can be done to unlock this synergy, we seek research on AI-driven predictive energy management, coupled chassis-and-powertrain control, edge computing applications, and advanced sensor fusion algorithms. Ultimately, this collection aims to accelerate the realization of highly efficient, resilient, and fully connected sustainable mobility solutions.

We welcome submissions exploring, but not limited to, the following themes:

o AI-empowered Battery Management Systems (BMS) and advanced thermal management
o Energy-efficient motion control and trajectory planning for autonomous EVs
o Architectures and system integration for Software-Defined Vehicles (SDVs)
o Multi-sensor fusion, robust perception, and decision-making algorithms
o Cloud-edge computing and low-latency Vehicle-to-Everything (V2X) communications

Submissions

We invite authors to contribute Original Research, Comprehensive Reviews, Mini-Reviews, and high-impact Case Studies that provide novel theoretical insights, robust methodologies, or practical engineering solutions to advance smart and sustainable mobility.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Keywords: Autonomous Driving, Electric Vehicles (EVs), Battery Management Systems (BMS), Software-Defined Vehicles (SDVs), Vehicle-to-Everything (V2X), Energy Management Strategy, Artificial Intelligence in Automotive, Sensor Fusion, Power Electronics, Cyber-Physical

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.