Adaptive Embedded Thermal Control System for Lithium-Ion Batteries in E-Bike

The rapid growth of electric vehicles has increased the demand for efficient and
reliable battery thermal management systems, especially for lithium-ion batteries used in
electric bikes. During charging and discharging, lithium-ion batteries generate a
significant amount of heat, which can lead to reduced efficiency, uneven temperature
distribution, battery degradation, and severe safety issues such as thermal runaway.
Conventional cooling systems used in electric vehicles are often expensive, bulky, non
adaptive, and unsuitable for compact applications like e-bikes. To address these
challenges, this project proposes an Adaptive Embedded Thermal Control System for
Lithium-Ion Batteries in E-Bike that combines embedded control, liquid cooling, and
IoT-based monitoring into a compact and energy-efficient solution.
The proposed system utilizes an ESP32 microcontroller as the central control unit for
real-time monitoring and adaptive thermal regulation. Temperature, current, and voltage
sensors continuously monitor the operating condition of the battery pack, while a
microchannel liquid cooling system using aluminium cold plates and water-ethylene
glycol coolant effectively dissipates excess heat. Based on the sensed battery
temperature, a Pulse Width Modulation (PWM)-based adaptive control algorithm
dynamically adjusts the coolant pump speed, ensuring efficient cooling only when
required and thereby reducing unnecessary power consumption.
To validate the effectiveness of the proposed design, thermal simulations and
performance analysis were carried out using ANSYS Fluent. The simulation results
demonstrated a significant reduction in battery temperature from nearly 50°C to
approximately 34°C, while also maintaining uniform temperature distribution across the
battery pack with minimal thermal variation. The optimized microchannel cooling
structure improved heat transfer performance and reduced hotspot formation, thereby
enhancing battery safety, reliability, and lifespan.
The developed system provides a practical, low-cost, and scalable thermal management
solution specifically suitable for electric bikes and other compact electric mobility
applications. By integrating adaptive cooling, embedded intelligence, and IoT-based
monitoring into a single platform.