| HEV has been the potential car to solve the environment issues and energy shortage, so an electricity energy storage device with high efficiency and long-life performance is the basis and foundation to make the most advantage of saving energy for hybrid vehicles. The peak power demand on battery is very high, requiring the battery should charge or discharge in a very short time, which may decrease lifespan of battery. The weakness of batteries blocked the development of HEV. Super-capacitor is a new kind of electricity energy storage, with high power density, efficiency, long life cycle and outstand capability to work at low temperature and high current. The use of battery-ultracapacitor could complement each other's advantages.This paper is tend to develop the hybrid energy storage on the basis of a collaborative project-'Study on the key technology of hybrid energy storage for HEV. In order to make electricity energy storages be well suited for the dynamic power demand of HEV well, we do some research on the requirement on battery of motor, and proposed new multi-objective optimization scheme for HEV based on genetic algorithm with the objective functions of minimizing both fuel consumption and the cost of storage.In the paper, a model of HEV with hybrid energy storage was built on basis of ADVISOR, and the constraint condition of design was proposed. Then a multi-objective optimization method NSGA_Ⅱwas employed on parameters match. At last, this paper developed a test bench, verified the advantages of hybrid energy storages.The paper includes following four aspects:1. Build the model of hybrid energy storage based on ADVISOR. Compared the topology of hybrid energy storage, a system with DC-DC converter between battery and the UC was chosen, in which the voltage of motor mainly depend on the voltage of battery. Having research on the characteristics of the components, a vehicle model with hybrid energy storage was established on the basis of ADVISOR.2. Research on the constraint conditions of design parameters. According the energy and power requirement of motor for electricity energy storage, the constraint condition was calculated.3. Multi-objective optimization of hybrid energy storage parameters. Elitist Non-dominated Sorting Genetic Algorithm (NSGA_Ⅱ) was used in the parameter design, with the objective functions of minimizing both fuel consumption and the cost of energy storage and a constraint of power performance. The simulation result showed that the fuel economy increased by 5% without the decrease of acceleration performance.4. Hybrid energy storage experiment verification. The paper built the prototype of hybrid energy storage and the test bench. The experiment result verified the feasibility of hybrid energy storage. Compared with single battery, the current of battery of hybrid energy storage reduced a lot.In this paper, Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ), one of the most efficient Multi-Objective Evolutionary Algorithms (MOEA), was used to optimize the parameters of the energy storage, with minimizing fuel consumption and the cost of energy storage and battery max current as objective functions. And the experiment result verified the advantages of hybrid energy storage on reducing the duty of battery. It could give reference to parameter match for hybrid power source on different type vehicle with different performance requirement. |
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