摘 要
电动汽车作为应对能源危机与环境污染的重要解决方案，其动力系统参数匹配与优化是提升车辆性能的关键。本研究聚焦于电动汽车动力系统参数匹配问题，旨在通过建立科学合理的参数匹配模型，实现对电池、电机等核心部件的最佳配置，以提高整车效率和续航里程。基于此目标，采用多学科交叉的研究方法，综合考虑动力学特性、热管理及成本因素，构建了包含电池容量、电机功率在内的多维度参数优化模型。创新性地引入了智能算法与仿真技术相结合的方式，通过对不同工况下的数据采集与分析，实现了对动力系统参数的精确匹配。结果表明，优化后的动力系统在加速性能、能耗水平等方面均有显著改善，特别是在城市工况下，续航里程提升了约15%，能量回收效率提高了10%。
关键词：电动汽车动力系统 参数匹配优化 智能算法与仿真
Abstract
As an important solution to deal with energy crisis and environmental pollution, the power system parameter matching and optimization of electric vehicles is the key to improve vehicle performance. This study focuses on the parameter matching problem of electric vehicle power system, aiming to achieve the best configuration of battery, motor and other core components by establishing a scientific and reasonable parameter matching model, so as to improve the efficiency and range of the vehicle. Based on this goal, a multi-dimensional parameter optimization model including battery capacity and motor power is constructed by considering the dynamic characteristics, thermal management and cost factors. It innovatively introduces the combination of intelligent algorithm and simulation technology, and realizes the accurate matching of power system parameters through the collection and analysis of data under different working conditions. The results show that the optimized power system has significantly improved in acceleration performance, energy consumption level and other aspects, especially in urban conditions, the range increased by about 15% and the energy recovery efficiency increased by 10%.
Keyword:Electric Vehicle Power System Parameter Matching Optimization Intelligent Algorithms And Simulation
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3研究方法与技术路线 2
2动力系统参数分析 2
2.1电动汽车动力源特性 2
2.2关键参数影响因素 3
2.3参数匹配理论基础 3
3参数匹配优化模型 4
3.1模型构建原则 4
3.2优化算法选择 5
3.3模型验证与评估 5
4实验与案例分析 6
4.1实验平台搭建 6
4.2参数匹配实验 7
4.3案例效果分析 7
结论 8
参考文献 9
致谢 10
