基于软计算优化的智能制造中的电动汽车动力系统.
1School of automotive engineering, Wuhan university of technology, Wuhan City, 430070, China.
Heliyon
|November 11, 2024
概括
这项研究使用基因算法 (GA) 来优化电动汽车的性能,提高动态能力超过7%并减少功耗损失5%. 增强型号允许电动汽车在相同的充电下行驶更远.
科学领域:
- 计算机工程 计算机工程
- 自动控制自动控制自动控制
- 软件计算 软件计算
背景情况:
- 软计算有效地解决了工程中的不确定性和复杂性.
- 遗传算法 (GA) 是解决复杂优化挑战的强大工具.
- 电动汽车 (EV) 性能优化对于效率和可持续性至关重要.
研究的目的:
- 通过软计算,共同优化电动汽车的动态和经济性能.
- 提高电动汽车能源管理策略和电力系统配置.
- 利用先进的算法来提高电动汽车的运营效率.
主要方法:
- 调查和分析电动汽车电力系统结构和能源管理.
- 应用改进的非主导排序遗传算法II (NSGA-II) 进行参数优化.
- 集成一个模糊逻辑控制器用于在线GA参数调整.
主要成果:
- 优化的电动汽车在动态性能方面表现出>7%的改进.
- 加速时间显著减少,功率损耗减少了5%.
- 该模型使电动汽车能够在相同的功率条件下实现更长的行驶距离.
结论:
- 该研究提出了一种通过软计算提高电动汽车性能的新方法.
- 优化的模型为电动汽车行业的智能制造提供了有价值的参考.
- 未来的电动汽车可以更高效,节能,环保.
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