Optimisation-Based Power Management System for an Electric Vehicle with a Hybrid Energy Storage System

Abstract

Hybridisation of energy storage sources is necessary for extending mileage of electric vehicles. However, coordination of multiple devices with different characteristics is challenging. This paper presents a power management system (PMS) for an electric car equipped with a battery pack, supercapacitor bank, and range extender. The proposed PMS deals with vehicular load distribution by solving a power management problem, formulated as a constrained quadratic program (CQP). Then, the optimised variables, such as the desired speed and optimised operation points of the car’s components, are implemented by controllers at a component level. Complete knowledge about the trip is unwanted because the proposed PMS considers a power management problem only over a controlled horizon of one sampling period. Furthermore, this work varies weight factors to tackle various difficulties, for instance, regenerative power management. The simulation results revealed that the proposed system optimally allocated an electric power load to the car components, without violating any physical constraints. Also, the comparative study showed that the performance of the CQP in power management was comparable to that of the benchmark, based on a nonlinear model predictive control.