Abstract
The parameter matching of composite energy storage systems will affect the realization of control strategy. In this study, the effective energy and power utilizations of an energy storage source were defined. With the miniaturization of a composite energy storage system as the optimization goal, the linear programming simplex method was employed to obtain the optimized masses of Li batteries and supercapacitors under the constraints of maximum speed, climbing gradient, acceleration time and cost-effectiveness. As the module numbers shall be integers, the matching results were modified in combination with the graphical method. Owing to the influences of parameter matching schemes on the overall performance and battery life, the critical points of constraints were analyzed and the most appropriate matching numerical points of the composite energy storage system were identified. Simulation and experimental analysis were conducted under practical urban road conditions in China. The results show that the proposed matching method delivers accurate results. Compared with conventional electric buses, the mileage and overall performance of the prototype bus are improved.
Highlights
The parameter design of hybrid energy storage systems (HESS) includes power capacity and energy capacity
With the development of battery and supercapacitors, researchers have committed to the matching and control strategy of composite energy storage sources consisting of supercapacitor packs and theoretical and practical explorations of applications of supercapacitors in electric vehicles
The results showed that the composite energy storage system can effectively provide driving power for motors [12,13]
Summary
The parameter design of hybrid energy storage systems (HESS) includes power capacity and energy capacity. The specific scheme was designed according to specific energy, specific power, cost, temperature range, reliability and safety of current energy storage source and optimized with a parameter of HESS as the optimization objective. Hu et al investigated the impacts of price fluctuation of a single energy storage component on the overall performance of vehicles using the convex optimization method, with cost as the optimization objective [16,17]. Harbin Institute of Technology proposed matching strategies based on optimization of the mass ratio and mixing ratio of electric vehicles. Jilin University proposed parameter optimization based on the measured data of vehicles, with charging/discharging capacity and service life of the HESS energy storage component as the optimization objectives [25,26]. From the perspective of requirements and evaluation indexes of power and costeffectiveness of vehicles, the influences of characteristic factors of the evaluation indexes, mass ratio of the HESS and conditions on vehicle performances were analyzed
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