Abstract
An integrated fault-diagnosis algorithm for a motor sensor of in-wheel independent drive electric vehicles is presented. This paper proposes a method that integrates the high- and low-level fault diagnoses to improve the robustness and performance of the system. For the high-level fault diagnosis of vehicle dynamics, a planar two-track non-linear model is first selected, and the longitudinal and lateral forces are calculated. To ensure redundancy of the system, correlation between the sensor and residual in the vehicle dynamics is analyzed to detect and separate the fault of the drive motor system of each wheel. To diagnose the motor system for low-level faults, the state equation of an interior permanent magnet synchronous motor is developed, and a parity equation is used to diagnose the fault of the electric current and position sensors. The validity of the high-level fault-diagnosis algorithm is verified using Carsim and Matlab/Simulink co-simulation. The low-level fault diagnosis is verified through Matlab/Simulink simulation and experiments. Finally, according to the residuals of the high- and low-level fault diagnoses, fault-detection flags are defined. On the basis of this information, an integrated fault-diagnosis strategy is proposed.
Highlights
Following the recent increase in international oil prices and environmental issues, studies on the introduction of environment-friendly vehicles such as fuel-cell and electric vehicles have increasingly become popular
The in-wheel independent drive electric vehicles contain motors installed inside the wheels, which feature enhanced system efficiency and driving performance [1,2,3,4]
The residuals obtained from Equation (19) and Figure 3 can be independently configured for each wheel and are listed as follows Table 1
Summary
Following the recent increase in international oil prices and environmental issues, studies on the introduction of environment-friendly vehicles such as fuel-cell and electric vehicles have increasingly become popular. Several studies regarding fault diagnosis of the in-wheel independent drive electric vehicles are being conducted using a planar two-track non-linear model [26,27,28,29,30,31]. In the present study, the diagnosis system integrates both the high-level fault diagnosis of the vehicle dynamics and low-level fault diagnosis of the motor system by considering the vehicle dynamic sensor faults to propose a method that increases the robustness and stability of the system. To increase the redundancy of the system, the correlation between the sensor and residual in the vehicle dynamics is analyzed to detect and separate the fault in the drive motor system in each wheel and the vehicle dynamic sensors such as the yaw-rate, longitudinal and lateral acceleration, and wheel-speed sensors.
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