PIL Implementation of a Fuzzy Energy Management Strategy for an Electric Vehicle with Battery and Supercapacitor

This paper presents the embedded implementation of a fuzzy logic-based multivariable energy management strategy for a hybrid storage system in electric vehicles (EVs), composed of a lithium-ion battery and a supercapacitor. The control system is designed to optimize power distribution based on driving demand and the state of charge of the storage devices. The approach aims to improve battery lifespan, reduce energy losses, and enhance overall system efficiency. The control algorithm is deployed on an ESP32 microcontroller using the Model-Based Design (MBD) methodology and tested in a Processor-in-the-Loop (PIL) configuration. The strategy was validated under standardized driving cycles (WLTCclasse3, ARTEMIS, and UDDS), achieving superior performance in cost minimization-reaching values as low as 72.159 in UDDS and 90.971 in WLTCclasse3-while also preserving higher final SoC values and minimizing unintended energy charged to the battery, indicating effective and robust energy management.