Dimensioning and Power Management of Hybrid Energy Storage Systems for Electric Vehicles With Multiple Optimization Criteria

Hybrid energy storage systems (HESS) that combine lithium-ion batteries and supercapacitors are considered as an attractive solution to overcome the drawbacks of battery-only systems, such high cost, low power density, short cycle life, which hinder popularity electric vehicles. A properly sized HESS implementable real-time management system great importance achieve satisfactory driving mileage battery life. However, dimensioning problems quite complicated challenging in practice. To address these challenges, this article proposes a bilevel multiobjective design control framework with nondominated sorting genetic algorithm NSGA-II fuzzy logic (FLC) key components, obtain optimal corresponding based on FLC simultaneously. In particular, vectorized inference is devised, allows large-scale controllers run parallel, thereby improving optimization efficiency. Pareto results different HESSs incorporating both parameters obtained efficiently thanks vectorization. An example chosen from front shows proposed method can competitive number covered laps while life significantly.