数字双胞胎的可信度评估在基于信息的循环测试中的车辆
Tianfang Gao1, Liang Chen1, Xinghui Zhang1
1Xiamen Product Quality Supervision and Inspection Institute, Xiamen 361023, China.
Sensors (Basel, Switzerland)
|March 17, 2025
概括
本研究引入了一种新的可信度评估方法,用于数字双胞胎在车辆在循环 (VIL) 测试中. 建议的基于信息的方法有效评估模型动态,并确定影响测试准确性的关键因素.
科学领域:
- 智能运输系统 智能运输系统
- 汽车工程 汽车工程
- 网络物理系统 网络物理系统
背景情况:
- 数字双胞胎对于智能汽车的开发和测试至关重要.
- 在汽车测试中,对于动态演变的模型缺乏有效的可信度评估.
- 车辆在循环 (VIL) 测试需要强大的方法来评估虚拟现实世界的互动.
研究的目的:
- 在VIL测试中开发数字双胞胎的可信度评估方法.
- 分析闭环动态虚拟和现实世界交互测试的特征.
- 确定影响数字双胞胎VIL测试准确性和可靠性的因素.
主要方法:
- 为动态虚拟和现实世界的互动构建了一个闭环测试.
- 提出了一种基于信息的可信度评估方法.
- 利用近似 (ApEn) 和交叉ApEn来量化信息的混和相关性.
主要成果:
- 拟议的算法通过实验成功验证.
- 在真实和数字车辆之间不一致的权重被确定为影响VIL测试可信度的重要因素.
- 时间序列数据的长度对可信度评估结果的影响很小 (≤2%).
结论:
- 基于信息的方法提供了一种有效的方法来评估VIL测试中的数字双胞胎可信度.
- 了解和管理权重不一致对于可靠的汽车VIL测试至关重要.
- 开发的方法为增强智能汽车的功能开发和评估提供了有价值的工具.
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