Journal of Electrical Engineering and Electronic TechnologyISSN: 2325-9833

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Editorial, J Electr Eng Electron Technol Vol: 14 Issue: 5

Electric Vehicle Powertrain Control: Enhancing Efficiency and Performance

Dr. Hiroshi Tanaka*

Dept. of Automotive Electronics, Kyoto Advanced Technology University, Japan

*Corresponding Author:
Dr. Hiroshi Tanaka
Dept. of Automotive Electronics, Kyoto Advanced Technology University, Japan
E-mail: h.tanaka@katu.jp

Received: 01-Sep-2025, Manuscript No. JEEET-26-183686; Editor assigned: 3-Sep-2025, Pre-QC No. JEEET-26-183686 (PQ); Reviewed: 17-Sep-2025, QC No. JEEET-26-183686; Revised: 24-Sep-2025, Manuscript No. JEEET-26-183686 (R); Published: 30-Sep-2025, DOI: 10.4172/2325-9838.10001020

Citation: Hiroshi T (2025) Electric Vehicle Powertrain Control: Enhancing Efficiency and Performance. J Electr Eng Electron Technol 14: 1020

Introduction

The global shift toward sustainable transportation has accelerated the adoption of electric vehicles (EVs), which promise reduced greenhouse gas emissions, lower operating costs, and improved energy efficiency. At the heart of every EV lies the powertrainâ??a system that converts electrical energy into mechanical motion. Effective control of the EV powertrain is crucial for optimizing vehicle performance, extending battery life, and ensuring safety under diverse driving conditions [1,2]. Advanced powertrain control strategies integrate motor control, energy management, and regenerative braking to maximize efficiency and provide a smooth, reliable driving experience.

Discussion

EV powertrain control involves coordinating various components, including the electric motor, inverter, battery pack, and transmission system. One of the primary objectives is motor control, which regulates torque, speed, and efficiency. Techniques such as field-oriented control (FOC) and direct torque control (DTC) allow precise manipulation of motor currents, enabling fast response, high efficiency, and reduced energy losses. These methods are essential for providing smooth acceleration and maintaining optimal performance across different driving scenarios [3,4].

Energy management

Energy management is another critical aspect of EV powertrain control. Battery energy is a limited resource, and efficient usage is essential for maximizing vehicle range. Control strategies monitor state-of-charge (SOC), state-of-health (SOH), and power demand to distribute energy intelligently between propulsion and auxiliary systems. Predictive energy management, often using machine learning or model-based algorithms, anticipates driving conditions, traffic patterns, and terrain to optimize battery usage in real time [5].

Regenerative braking

Regenerative braking further enhances powertrain efficiency by converting kinetic energy into electrical energy during deceleration. Effective control algorithms determine the optimal balance between mechanical braking and regenerative braking to maximize energy recovery without compromising vehicle stability. Integration with motor and battery management systems ensures safe and efficient operation while improving overall energy efficiency.

Advanced control functions

Advanced powertrain control also supports vehicle stability, thermal management, and fault detection. By continuously monitoring component temperatures, electrical loads, and system performance, the control system can prevent overheating, manage stress on the battery, and detect anomalies before they lead to failure. This comprehensive control ensures reliability, safety, and longevity of the EV powertrain.

Conclusion

Electric vehicle powertrain control is a cornerstone of efficient, reliable, and high-performance electric mobility. By integrating precise motor control, intelligent energy management, and regenerative braking, advanced control systems enhance driving range, safety, and overall vehicle efficiency. As EV technology continues to evolve, innovations in powertrain control will be critical to meeting the demands of next-generation electric transportation, supporting both environmental sustainability and consumer satisfaction.

References

  1. Tarle S, Kakad A, Shaikh M (2023) Overview: Embracing tools of artificial intelligence in pharmaceuticals. Int J Sci Acad Res 4: 5749-55.

    Indexed at, Google Scholar, Crossref

  2. Meske C, Bunde E, Schneider J, Gersch M (2022) Explainable artificial intelligence: objectives, stakeholders, and future research opportunities. Information Systems Management 39: 53-63.

    Indexed at, Google Scholar, Crossref

  3. Shakya S (2020) Analysis of artificial intelligence-based image classification techniques. Journal of Innovative Image Processing (JIIP) 2: 44-54.

    Indexed at, Google Scholar, Crossref

  4. Yu MC (2011) Multi-criteria ABC analysis using artificial intelligence-based classification techniques. Expert Systems with Applications 38: 3416-3421.

    Indexed at, Google Scholar, Crossref

  5. Sharma T, Mankoo A, Sood V (2021) Artificial intelligence in advanced pharmacy. International Journal of Science and Research Archive 2: 047-054.

    Google Scholar

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