预测喜欢的摩托车骑行姿势,以支持人为因素/人体工程学权衡分析,在基于多目标优化的数字人体模型中进行分析
Justin B Davidson1, Dr Steven L Fischer1
1Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada.
Ergonomics
|March 18, 2024
概括
数字人类模型 (DHM) 有助于预测用户与新车辆设计的互动. 尽量减少不适,包括关节运动范围和扭矩,在DHM模拟中最好预测首选的摩托车骑行姿势.
科学领域:
- 人体工程学和人类因素
- 汽车设计 汽车设计
- 计算建模 计算建模
背景情况:
- 数字人类模型 (DHM) 对于车辆设计的早期阶段至关重要,它可以预测用户与新几何相互作用.
- 在DHM中准确预测人类姿势需要了解影响用户偏好的性能标准.
- 驾驶偏好的摩托车骑行姿势的具体性能标准在很大程度上是未知的.
研究的目的:
- 确定使用DHM的关键性能标准及其权重,以最好地预测使用DHM的首选摩托车行驶姿势.
- 解决关于影响摩托车骑手姿势预测在数字环境中的因素的知识差距.
主要方法:
- 文献综述,收集关于偏好的摩托车骑行姿势 (联合角度) 的实验数据.
- 用于优化DHM姿势预测的性能标准和权重的响应表面方法.
- 分析的重点是关节运动范围,偏离中性和关节扭矩等标准.
主要成果:
- 尽量减少不适成为最重要的绩效标准.
- 确定了与不适相关的因素的最佳权重,包括关节运动范围,偏离中性和关节扭矩.
- 这种方法在DHM框架内成功预测了首选的摩托车骑行姿势.
结论:
- 在DHM模拟中,尽量减少骑手不适是首选摩托车骑行姿势的主要驱动因素.
- 该研究提供了一种有效的方法来优化DHM参数,以准确地反映骑手在摩托车设计中的偏好.
- 这些发现有助于在汽车行业中更现实的和有效的早期设计权衡分析.
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