Thermal Regulation in the Battery Pack of Electric Vehicle By Adaptive Speed Control

Abstract

Electric vehicle battery performance and lifespan are critically dependent on effective thermal management, with excessive temperatures leading to accelerated degradation and safety risks. While most existing systems employ active cooling methods, this study investigates an alternative approach using adaptive speed control as a means of passive thermal regulation. The proposed model focuses on controlling energy discharge rates through motor speed modulation based on real-time temperature feedback, offering a potentially simpler and more energy-efficient solution compared to conventional cooling systems. This paper presents a simulation-based implementation of a thermal regulation system that adjusts vehicle speed in response to battery temperature variations. The core innovation lies in using field-oriented control (FOC) of the traction motor to limit battery current when temperatures approach critical thresholds. A mathematical model establishes the relationship between speed reduction and consequent heat generation decrease, demonstrating how controlled power output can maintain safe operating temperatures. The control architecture incorporates temperature sensor inputs processed by an Arduino Uno microcontroller, which calculates appropriate speed references to prevent thermal overload while maintaining basic vehicle functionality. Key aspects of the implemented model include: (1) a battery thermal dynamics representation accounting for ohmic heating and ambient conditions, (2) a speed control algorithm that prioritizes thermal protection during high-temperature scenarios, and (3) a simulation framework evaluating system response under various driving cycles. The results indicate that strategic speed reduction can effectively mitigate temperature spikes during demanding operation, particularly in stop-and-go urban conditions where active cooling systems are least efficient. The study provides theoretical validation for a novel thermal management paradigm that replaces energy-intensive cooling components with intelligent power limitation. While not yet implemented on a physical prototype, the simulation outcomes suggest significant potential for reducing system complexity and energy consumption in EV thermal management. Future work will focus on hardware implementation, including battery pack instrumentation and real-world performance validation, as well as optimization of the control algorithms for different environmental conditions

Introduction

Summary:

The rising adoption of electric vehicles (EVs) highlights critical challenges in battery thermal management, where overheating can impair performance, reduce battery life, and pose safety risks. Passive cooling systems are simple and cost-effective but insufficient under high thermal loads. This study introduces a novel thermal-aware speed control strategy for the Permanent Magnet Synchronous Motor (PMSM) in EVs, which adaptively reduces motor speed only when the battery temperature exceeds a set threshold. This approach minimizes battery heat generation, allowing passive cooling to be more effective without energy-intensive active cooling.

The literature review covers advanced battery thermal management techniques, including phase-change materials, direct liquid cooling, and IoT-based smart battery systems. It also highlights the integration of thermal management with EV subsystems for energy optimization and discusses challenges in commercial scalability and gendered toy marketing.

The methodology details the use of real-time temperature monitoring and adaptive control algorithms to dynamically manage motor speed for battery protection while maintaining vehicle performance. The PMSM motor, favored for EV propulsion due to its efficiency and power density, is modeled in MATLAB Simulink, incorporating electrical, mechanical, and control dynamics. The study uses Field-Oriented Control (FOC) for precise speed and torque control, supported by Park and Clarke transformations to simplify motor control.

Hardware interfacing is achieved via Arduino integrated with Simulink, enabling real-time sensor data acquisition and control algorithm deployment. This setup facilitates rapid prototyping, live data visualization, and hardware-in-the-loop testing, making it suitable for research and educational purposes.

Overall, the proposed strategy advances integrated thermal and motor control for EVs, optimizing passive cooling and improving battery safety and vehicle efficiency.

Conclusion

This study proposed a novel passive cooling strategy for electric vehicle (EV) battery packs by integrating adaptive speed control via Field-Oriented Control (FOC) to regulate heat dissipation. Instead of active cooling mechanisms, the system dynamically adjusts the motor’s reference speed based on battery temperature, reducing power draw and internal heat generation when critical temperatures are exceeded. A MATLAB simulation demonstrated the effectiveness of FOC-based speed regulation, where an Arduino Uno provided reference speed inputs by analyzing real-time battery temperature and motor speed. The results indicate that this approach can effectively mitigate thermal buildup without additional cooling hardware, enhancing battery longevity and safety. Future work will incorporate battery pack thermal modeling to further optimize the control strategy under varying driving conditions.

References

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Copyright

Copyright © 2025 Muthuram G, Vishnuprakash R, Nithish Joyal A, Devendran M, Pavan Kumar S. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.