Modelling Techniques and Power Management Strategies for Dual Battery Systems in Electric Vehicles - A Review

Dual battery systems in Electric Vehicles (EVs) represent a significant advancement in optimising energy storage, power management, and vehicle performance. These systems combine two distinct batteries, often with different chemistries or capacities, to meet varying energy demands, improve efficiency, and extend battery lifespan. This review provides an in-depth analysis of the current modelling techniques and power management strategies used in dual battery systems. The modelling techniques explored include electrochemical models, Equivalent Circuit Models (ECM), data-driven models, and thermal models. Each modelling approach has distinct advantages and limitations depending on its application. For example, electrochemical models offer high accuracy in simulating battery behaviour but require substantial computational power, making them less suitable for real-time applications. In contrast, ECMs provide a simplified yet effective representation of battery performance, ideal for practical implementations in EVs. Power management strategies, including rule-based, optimisation-based, and predictive methods, are essential for managing the complexities of dual battery systems. Rule-based power management is cost-effective and simple but lacks the flexibility and efficiency of more advanced methods. Optimisation-based strategies use mathematical algorithms to dynamically distribute power between batteries, achieving higher efficiency. Predictive power management, such as Model Predictive Control (MPC), anticipates future driving conditions and adjusts battery usage in real-time, ensuring optimal performance and extended battery life. Additionally, the integration of energy harvesting systems, such as regenerative braking, further enhances the efficiency of dual battery configurations. Major Findings: The review highlights that dual battery systems, combining different chemistries, significantly enhance EV energy efficiency, power management, and battery life. Advanced modelling and predictive power management strategies are key to optimising performance, while integrating energy harvesting systems further boosts efficiency.