Automatic test equipment for electric vehicle components

电动汽车零部件自动测试设备

• 批准号: 530656-2018
• 负责人: Rashidzadeh, Rashid
• 金额: $ 1.28万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=663017
• 关键词: Automatic; test; equipment; electric; vehicle

The auto-industry has high standards for engine parts. All main parts have to be accurately measured to ensure their geometrical characteristics [1]. For certain parts the acceptable variation of geometrical features and dimensions from nominal values is less than a few micrometers. A part that does not meet the measurement requirements can result in premature wear, transmission problem or even catastrophic engine failure. Coordinate Measuring Machines (CMMs) are widely used to measure geometrical features of engine parts. Commercially available CMM machines measure dimensions by collecting data using a sensing device or probe. CMM machines have been used to measure transmission parts of combustion engine cars. As the technology advances from combustion engine to Electric Vehicles (EV) the engine parts measurement become more challenging. The engine noise in EV is very low to the degree that is difficult to hear if an electric vehicles is ON or OFF. To maintain such a low level of noise, the variations of geometrical dimensions for engine parts from their nominal values have to be less than a few micrometers. Such a measurement accuracy cannot be easily achieved by current CMM machines. The main objective of this work is to design a non-contact CMM machine for electric vehicle parts with auto learning capacity to meet the measurement accuracy and resolution requirements for new generation of electric cars. If the proposed system is employed in the production line the benefit to the Canadian industry will be significant as it reduces the time required to test electric vehicle parts considerably. The potential sales of the family of products within this platform technology is expected to exceed $10M over its life. ****

汽车工业对发动机部件有很高的标准。所有主要部件都必须精确测量，以确保其几何特性[1]。对于某些零件，几何特征和尺寸与标称值的可接受变化小于几微米。不符合测量要求的零件可能导致过早磨损、传动问题甚至灾难性的发动机故障。三坐标测量机（CMM）被广泛用于测量发动机零件的几何特征。市售的CMM机器通过使用感测装置或探针收集数据来测量尺寸。三坐标测量机已被用于测量内燃机汽车的传动部件。随着技术从内燃机向电动汽车的发展，发动机零件的测量变得越来越具有挑战性。电动汽车的发动机噪音非常低，以至于电动汽车在ON或OFF时很难听到。为了保持如此低的噪声水平，发动机部件的几何尺寸与其标称值的变化必须小于几微米。这样的测量精度不能通过当前的CMM机器容易地实现。本课题的主要目标是设计一种具有自学习能力的电动汽车零部件非接触式三坐标测量机，以满足新一代电动汽车对测量精度和分辨率的要求。如果在生产线上采用拟议的系统，对加拿大工业的好处将是显着的，因为它大大减少了测试电动汽车部件所需的时间。 该平台技术中产品系列的潜在销售额预计将超过1000万美元。****