电动汽车传动系统的匹配及优化-车辆工程专业论文.docxVIP

电动汽车传动系统的匹配及优化-车辆工程专业论文.docx

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电动汽车传动系统的匹配及优化-车辆工程专业论文

哈尔滨工业大学工学硕士学位论文 哈尔滨工业大学工学硕士学位论文 - - II - Abstract There were increasing concerns about environmental and energy problems, electric vehicles have been developed for its benefit of zero emission and low noise. Many countries make electric vehicles as the development direction of automobile industry. Recently, although there are lots of countries which have launched into large fund and many talents to study electric vehicles, dynamic battery and certain key techniques have not brought through effectively until now. The range and charging time of battery limited popularization and development of electric vehicles. Therefore how to select these parts and relational parameters reasonably makes the electric vehicle meet the request of dynamic performance and range, which is the goal people studied, then which is the important content of the papers. In this thesis, the method and principle of parameters design for electromotor, the ratio of power train and batteries capacity of electric vehicles were explored and discussed. Based on some type of EV, the parameters of power train of EVS were selected and designed more reasonably and pithily. This thesis studied key pacts’ mathematics models of EV, such as electromotor, battery. Moreover, simulation models of whole vehicle and key pacts, such as battery, electromotor, vehicle body were built in EV dynamic simulation soft of advanced vehicle simulator (ADVISOR). Then the dynamic performance of EVS was simulated with the soft of ADVISOR. The simulation results have demonstrated that the designed parameters and the simulation models are rational. Additionally, in the virtue of analyzed simulation result and the requests of dynamic performance and range, the thesis optimized certain main parameters utilizing design parameters optimization method of automobile power train on the basis of genetic algorithm (GA) and Auto-size in ADVISOR, motor efficiency, battery capacity, transmission ratio etc. Meanwhile, optimization result was

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