通过局部敏感的散列变压器和间隔分析预测和优化纯电动汽车道路噪声
Mingliang Yang1, Peisong Dai1, Yingqi Yin1
1School of Mechanical Engineering, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China.
ISA transactions
|December 12, 2024
概括
纯电动汽车 (PEV) 已经减少了发动机噪声,但道路噪声变得更加突出. 这项研究引入了一种新的方法来预测和优化PEV道路噪声,改善室内声学超过2dB.
科学领域:
- 汽车工程 汽车工程
- 声学 声学 声学 声学
- 数据科学数据科学数据科学
背景情况:
- 纯电动汽车 (PEV) 消除了发动机噪音,导致更安静的车.
- 然而,发动机噪声的缺失凸显了其他来源,特别是道路噪声.
- 道路噪声对PEV中中低频室内噪声产生重大影响.
研究的目的:
- 提出一种新的方法来预测和优化PEV中的道路噪声.
- 通过解决道路噪声的主要来源来提高室内噪声质量.
- 通过不确定性分析,提高噪声优化的稳定性和有效性.
主要方法:
- 使用了具有精细注意力机制和局部敏感哈希的变压器模型,用于准确的道路噪声预测.
- 开发了一种包含参数不确定性的间隔向量优化方法,以获得可靠的结果.
- 通过在纯电动汽车上进行道路测试来验证拟议的方法.
主要成果:
- 精细的注意力机制提高了预测频域道路噪声特征的效率和准确性.
- 间隔向量优化方法提高了降噪策略的稳定性.
- 在PEV中优化噪声条件显示了超过2dB的显著改善.
结论:
- 提出的数据驱动方法有效地预测和优化PEV中的道路噪声.
- 将先进的AI与不确定性分析相结合,为增强车辆内部声学提供了强大的解决方案.
- 经过验证的方法显著降低了有害的道路噪音,改善了电动汽车的整体驾驶体验.
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