Adaptive Duty Cycle Control for Safe and Efficient EV Fast Charging

Abstract

Electric Vehicle (EV) charging technology currently faces critical challenges related to slow charging speeds and safety risks associated with overheating. Traditional Battery Management Systems (BMS) often lack the real-time adaptability required to handle rapid temperature fluctuations during high-current charging scenarios. This paper proposes an intelligent external control system designed to ensure fast, safe, and efficient battery charging by integrating a Dynamic Duty Cycle (DDC) control circuit with the existing BMS infrastructure. Utilizing an ESP32 microcontroller as the central processing unit, the system monitors the rate of temperature change (dT/dt) in real-time and employs automatic relay switching to manage thermal loads effectively. Theoretical analysis using the Arrhenius aging law validates that this approach significantly reduces battery degradation mechanisms. Furthermore, the hardware implementation demonstrates effective thermal peak clipping, ensuring the battery operates within safe thermal limits while optimizing the overall charging duration.

Introduction

The widespread adoption of electric vehicles (EVs) is limited by challenges in battery charging infrastructure, particularly the thermal bottleneck that occurs during fast charging. High charging currents generate excessive heat within lithium-ion batteries through Joule heating and electrochemical reactions, increasing the risk of thermal runaway, fires, and accelerated battery degradation. Conventional Battery Management Systems (BMS) typically use fixed charging methods such as Constant Current–Constant Voltage (CC-CV), which do not adequately respond to rapid temperature changes during high-rate charging.

This project proposes an intelligent external thermal management system that works alongside the vehicle’s existing BMS. The system uses an ESP32 microcontroller for real-time temperature monitoring and automatically switches control between the internal BMS and an external Dynamic Duty Cycle (DDC) control circuit. By continuously monitoring the rate of temperature increase (dT/dt), the system dynamically adjusts the charging duty cycle, balancing charging speed with thermal safety. The goal is to prevent overheating and extend battery lifespan.

The literature review highlights the importance of active thermal management in EV batteries. Previous studies have explored predictive thermal models, machine learning-based temperature estimation, and thermal behavior analysis. While these approaches improve safety and accuracy, many require high computational power, large datasets, or expensive hardware, limiting their practicality for low-cost applications. Research also confirms that elevated temperatures significantly accelerate battery aging, with every 10°C increase potentially reducing battery life by half.

To address these limitations, the proposed system offers a computationally efficient hardware-based solution using a standard ESP32 microcontroller. Its theoretical framework is based on battery thermodynamics, where temperature changes depend on the balance between heat generation and heat dissipation. The DDC controller introduces controlled charging “OFF” periods whenever the battery temperature rises too quickly, allowing heat to dissipate and preventing dangerous thermal peaks.

Conclusion

This project successfully developed a smart charging mod-ule that integrates Dynamic Duty Cycle control with standard BMS functions. The ESP32-based system provides real-time monitoring and adaptive control, mitigating overheating risks. The theoretical analysis using the Arrhenius law and thermal balance equations, combined with hardware validation, con-firms that the DDC approach extends battery life and enhances safety. The proposed modular PCB design offers a scalable platform for future EV battery management research.

References

[1] Z. Lu et al., “Integrated Optimal Fast Charging and Active Thermal Man-agement of Lithium-Ion Batteries in Extreme Ambient Temperatures,” IEEE Trans. Power Electron., Mar. 2025. [2] D. Karnehm et al., “Core Temperature Estimation of Lithium-Ion Batter-ies Using Long Short-Term Memory (LSTM) Network and Kolmogorov-Arnold Network (KAN),” IEEE TechRxiv, 2024. [3] C. Bibin et al., “A review on thermal issues in Li-ion battery and recent advancements in battery thermal management systems,” Mater. Today: Proc., vol. 33, 2020. [4] F. Leng et al., “Effect of temperature on the aging rate of Li-ion batteries operating above room temperature,” Sci. Rep., vol. 5, 2015. [5] C. Chen et al., “Critical understanding of temperature gradient during fast charging of lithium-ion batteries,” IEEE, 2023. [6] J. Jaguemont et al., “Thermal modeling of Li-ion battery systems for electric vehicles,” Renew. Sustain. Energy Rev., vol. 117, 2020.

Copyright

Copyright © 2026 Adikrishna S, Basil Baby, Caren Viji Mathew, Sooraj R, Neethu Salim, Jeena Joy. 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.