Development of battery-supercapacitor management systems for electric vehicles

Abstract

The electric vehicle (EV) sector is rapidly advancing, representing a global shift toward sustainable, eco-friendly transportation. With an increasing focus on reducing carbon emissions and reliance on fossil fuels, EVs have become central to achieving environmental goals. However, widespread adoption is challenged by current limitations in energy storage, efficiency, and reliability. This thesis introduces an innovative hybrid energy storage system (HESS) tailored for EVs, integrating both batteries and supercapacitors to overcome these limitations. At the core of this HESS lies a battery management system (BMS) responsible for monitoring, optimising, and sustaining battery health and performance. The BMS is critical for ensuring safe operation, extending battery life, and maximising energy efficiency across a range of operational conditions. This study tackles three principal difficulties in electric vehicle energy management: the efficient integration of HESS, operating stability, and improved efficiency under varying driving situations. The research examines various battery types, such as lead-acid, nickel-cadmium, nickel-metal-hydride, and lithium-ion, evaluating each for energy density, power output, lifespan, and charging efficiency. Lithium-ion batteries, commonly utilised in electric vehicles for their high energy density and consistent performance, are assessed for their compatibility with supercapacitors in hybrid energy storage systems. Supercapacitors, recognised for their quick charge-discharge capabilities and enhanced power density, augment lithium-ion batteries by alleviating stress during peak power demands. The resultant HESS design integrates the advantages of both components, providing a system that enhances efficiency while ensuring sustained performance and dependability in electric vehicles. A novel contribution of this research is the development of a fully active HESS topology, capable of dynamic energy allocation to reduce stress on the battery and SC. Three common driving cycles were used in the simulations, including Artemis Rural, Artemis Motorway, and US06, to reflect varied driving situations. The simulations were performed using MATLAB/Simulink. In comparison with Proportional-Integral (PI) and Model Predictive Control (MPC) approaches, the results show that the Radial Basis Function (RBF) controller optimises energy flow and maintains system stability significantly. The RBF controller obtained a battery State of Charge (SOC) of 78.86% with the HESS in the Artemis Rural cycle, which is far higher than the 64.41% and 64.2% SOCs achieved by the MPC and PI controllers, respectively. In comparison to the MPC controller's 99.28% and the PI controller's 99.14% SOC, the RBF controller achieved a minimal SOC loss of 99.69% during the Artemis Motorway cycle. The RBF controller outperformed the MPC controller at 72.75% and the PI controller at 70.2% in the demanding US06 cycle, which is characterised by rapid acceleration and deceleration, by maintaining a SOC of 82.91%. Moreover, the RBF controller obtained a substantial energy savings of 3.09 kWh in the US06 cycle when contrasted with the PI controller. The RBF controller is the most effective strategy for optimising HESS performance across a variety of operating conditions, as these results demonstrate. The findings emphasise the HESS's ability to mitigate battery stress, optimise energy recovery, and ensure stable performance across varied driving conditions. The HESS minimises energy losses, enhances energy recovery efficiency, and extends battery lifespan by dynamically allocating energy between the battery and supercapacitor. These results establish benchmarks for the integration of HESS in EVs, contributing to sustainable transportation solutions.