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Parameter Estimation in Analytical Models of Automotive Vehicles and Fault Diagnosis

机译:机动车分析模型中的参数估计与故障诊断

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摘要

A global model based method for fault detection and physical diagnostics is developped using parameter estimation-identification in automotive problems. The procedure has been specifically tested on analytical models of the dynamical behaviour of lateral motion comprising rail-yaw attitude and front-rear and center of mass sideslips dynamics in which all the parameters have a physical sense and later on models of specific absorbers. Typical faults' examples corresponding to physical parameter subsets that can be detected and diagnosed are suspension stiffness and damping coefficients, front and rear sideslip stiffnesses, load and inertia mismatches,... and diverse combination of them for the the lateral motion and specific friction terms for the shock absorbers.
机译:利用汽车故障中的参数估计识别技术,开发了一种基于全局模型的故障检测和物理诊断方法。该程序已在横向运动动力学行为的分析模型上进行了专门测试,该模型包括钢轨偏航姿态以及前后和质心侧滑动力学,其中所有参数都具有物理意义,随后在特定的吸收体模型上进行了测试。可以检测和诊断的对应于物理参数子集的典型故障示例包括悬架刚度和阻尼系数,前后侧滑刚度,载荷和惯性不匹配,以及它们在横向运动和比摩擦项方面的各种组合用于减震器。

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