Optimal Power Management of an e-Racing Vehicle

Abstract

The Motor Vehicles Challenge, organized by the IEEE Vehicular Technology Society, is an annual competition focused on the development of advanced energy management strategies to enhance electric vehicle (EV) performance. In the 2024 edition, the study focused on detailed modeling of powertrain losses, particularly in high-efficiency silicon carbide-based power converters and internal permanent magnet (IPM) motors. The system under consideration is a high-performance electric racing vehicle equipped with a hybrid energy storage system (HESS) that integrates lithium-ion batteries and supercapacitors. The primary control objective is to minimize energy consumption and powertrain losses while satisfying thermal, electrical, and operational constraints. Equivalently, this objective can be formulated as maximizing the total energy stored at the final time in both the battery and the supercapacitor. To achieve this, two optimal control approaches were investigated: Pontryagin’s Minimum Principle (PMP) and Dynamic Programming (DP). While PMP provides efficient, locally optimal solutions based on necessary conditions, DP offers globally optimal control policies by exploring the entire state space at the expense of increased computational complexity. The comparative results highlight the trade-off between real-time feasibility and global optimality, providing valuable insights into energy-efficient control of high-performance EVs.