Abstract
In this paper, the ADVISOR software was used to establish a complete vehicle model of an electric vehicle, and the model was verified by CYC_NEDC under European urban conditions to meet the requirements. The maximum power of the driving motor, the speed ratio of the transmission system and the capacity of the storage battery are taken as the optimization objectives to carry out multi-objective optimization. Connect the model built by genetic algorithm and ADVISOR, run the program to simulate the two together, and get the result of parameter optimization of dynamic system. Through the simulation analysis and comparison under CYC_NEDC cycle conditions, the maximum speed, maximum climb slope, acceleration time and other dynamic performance parameters of this electric vehicle are effectively improved after optimization.
Highlights
For pure electric vehicles, how to design the power system and optimize the parameters so that they can achieve the best power performance under different driving conditions, meet the maximum speed, acceleration and climbing requirements
The parameter optimization model is established. 3.1 Modeling 3.1.1 Selected Variable In this paper, the maximum power Pmax of the drive motor, the transmission ratio I 0 and the battery capacity C are selected as optimization variables to ensure the optimal dynamic performance of the vehicle during the driving process, the selected variables are as follows:
Based on the above modeling, the ADVISOR simulation model is called by genetic algorithm, and the ADVISOR performance is calculated by assigning optimization variables, and the optimization objective function is calculated, optimization complete
Summary
How to design the power system and optimize the parameters so that they can achieve the best power performance under different driving conditions, meet the maximum speed, acceleration and climbing requirements. For the optimization of power system parameters of pure electric vehicle, the transmission speed ratio is mainly chosen as the optimization design variable. 3.1 Modeling 3.1.1 Selected Variable In this paper, the maximum power Pmax of the drive motor, the transmission ratio I 0 and the battery capacity C are selected as optimization variables to ensure the optimal dynamic performance of the vehicle during the driving process, the selected variables are as follows:. 3.1.2 Establish an Optimal Objective Function The optimization objectives of power performance of pure electric vehicle mainly include the vehicle’s maximum speed UAMAX, maximum climbing degree Imax, and minimum acceleration time T.
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