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Fault Diagnosis for Electric Drive Systems of Electrified Vehicles Based on Structural Analysis

机译:基于结构分析的电动汽车电力驱动系统故障诊断

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Functional safety is of great importance for electric and hybrid electric vehicles (EV/HEVs). One way to improve functional safety of EV/HEVs is to develop reliable and robust onboard diagnostics (OBD) so that, once a component fault is detected, effective remedial actions are taken to avoid system failures. In this paper, we develop a systematic model-based diagnostic approach based on structural analysis for electric drive systems that can form the basis of OBD design for EVs. The structural analysis approach for fault detection and isolation (FDI) evaluates a system's structural model, using the mathematical model of the system in matrix form, from which it is possible to determine the analytic redundancy and to design the structured residuals. In this paper, we demonstrate the application of this methodology by carrying out the design of a diagnostic approach for permanent-magnet synchronous machine (PMSM) drive systems of EVs, with specific focus on sensor fault diagnosis. The diagnostic approach is first verified through a simulation study on the EcoCAR2 vehicle, which is a plug-in HEV developed by the Center for Automotive Research at The Ohio State University, and is then further validated through an experimental study on a test bench consisting of a three-phase inverter enabled by the TMS320F28035 digital signal processor and a PMSM.
机译:功能安全对于电动和混合动力电动汽车(EV / HEV)至关重要。改善EV / HEV的功能安全性的一种方法是开发可靠而强大的车载诊断程序(OBD),这样,一旦检测到组件故障,便会采取有效的补救措施来避免系统故障。在本文中,我们基于电力驱动系统的结构分析开发了一种基于模型的系统诊断方法,该方法可构成电动汽车OBD设计的基础。故障检测和隔离(FDI)的结构分析方法使用矩阵形式的系统数学模型来评估系统的结构模型,从中可以确定分析冗余并设计结构化残差。在本文中,我们将通过对电动汽车的永磁同步电机(PMSM)驱动系统进行诊断的方法设计来论证该方法的应用,特别侧重于传感器故障诊断。该诊断方法首先通过对EcoCAR2车辆的仿真研究进行验证,EcoCAR2车辆是由俄亥俄州立大学汽车研究中心开发的插电式混合动力汽车,然后通过在由以下人员组成的测试台上进行的实验研究进一步得到验证: TMS320F28035数字信号处理器和PMSM支持的三相逆变器。

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