技术
- 机器人 - 自动导引车 (AGV)
- 传感器 - 触觉传感器
适用行业
- 汽车
- 包装
适用功能
- 产品研发
用例
- 智能停车
- 车辆性能监测
服务
- 系统集成
关于客户
Crimson Racing 是阿拉巴马大学的 Formula SAE 车队,成立于 2001 年。他们曾参加过美国各地的 Formula SAE 赛事,包括密歇根州、内布拉斯加州和弗吉尼亚州的赛事。该车队拥有 Formula SAE 近二十年的历史,过去五年是车队历史上最成功的五年。这一成功归功于对赛车上每个组件的理解和合理性的一致关注。 Crimson Racing 近年来取得了显着进步,将车重减轻了近 200 磅,并从常年排名第 90 的车队晋级到 2017 年的前 20 名车队。他们为自己设定了雄心勃勃的目标,旨在进入 FSAE 前 10 名密歇根州。
挑战
Crimson Racing 是阿拉巴马大学的 Formula SAE 车队,近二十年来一直参加美国各地的 Formula SAE 赛事。尽管有着悠久的历史,但该车队最成功的几年是过去五年,这要归功于对赛车每个部件的理解和论证。该团队取得了重大进步,车辆重量减轻了近 200 磅,并从常年排名第 90 的队伍跃升至 2017 年前 20 的队伍。然而,他们设定了一个雄心勃勃的目标,要在 FSAE 密歇根州进入前 10 名,这需要击败了世界上许多最好的球队。为了实现这一目标,他们决定在车辆上添加前翼和后翼。这一变化虽然对空气动力学意义重大,但也影响了车辆的结构,增加了负载,提高了重心,并增加了动力总成系统必须克服的阻力。悬架团队必须重新验证每个承载悬架部件,以确保满足足够的强度和刚度要求,这在分析三维运动的零件时是一项复杂的任务。
解决方案
为了估计悬架的力输入,该团队创建了一个内部工具,用于在给定基本车辆尺寸、重量和运动学特性的情况下估计车辆性能。通过该工具,可以估计转弯、制动和加速以及各种速度的组合场景中的最大轮胎负载。在 Altair 多体动力学软件 MotionSolve 的帮助下,该团队能够通过导入几何点、弹簧刚度、防倾杆刚度和阻尼系数来构建前后悬架模型。使用这些参数,创建刚体来代表所有相关的悬架部件。然后将从工具中找到的预期负载设置为施加在接触面上的力。最后,虚拟传感器被放置在所有悬架接头上,以便可以在 Altair 的后处理器 HyperView 中记录和查看力和扭矩。在 Altair 的帮助下,该团队能够采用多项设计变更,显着减少通过前拉杆传递的高负载以及作用在摇杆上的相应高力矩的问题。
运营影响
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