Dynamic Energy Optimization for Electric Vehicle Propulsion Using Fuzzy Logic

Energy Management Systems (EMS) are pivotal in optimizing the performance and efficiency of battery electric vehicles (BEVs) by intelligently distributing power within the vehicle's components. This work aims to design an EMS approach utilizing a dynamic coefficient controlled by a Fuzzy Logic Controller (FLC) to manage the energy distribution of the propulsion systems based on driving conditions and vehicle demands. The FLC operates on six critical input variables-vehicle velocity, state of charge (SOC), road slope, ambient temperature, vehicle weight, and driving mode-to adaptively modulate the energy supplied to the electric motor. Validation of this EMS through real-world data demonstrates the FLC's capability to significantly enhance electric vehicle efficiency and responsiveness across various operational conditions.