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This paper introduces the development and calibration process of a vehicle drivetrain observer used in hybrid and electric vehicles for active damping control (ADC) and for the improvement of the electric machine's rotor angle signal quality. This approach starts with creating an overall vehicle model that includes the electric machine, the transmission, side shafts, the tires and the vehicle body. For control engineering purposes, that multi-order-model is then reduced into a two-mass-oscillator which can be easily described in state-space form. Using this reduced drivetrain model and applying a Luenberger observer approach, not only the signal quality of both the instrumented rotor angle and the speed of the electric machine can be improved considerably but also the oscillation dynamics of this vehicle drivetrain can be estimated. If not compensated during vehicle operation, drivetrain oscillations might lead to increased drivetrain wear, NVH issues and limited ride comfort; therefore, the oscillation speed is very important in computing an active damping torque that is to compensate drivetrain oscillations. Calibration of the vehicle drivetrain observer is done using specific vehicle test data that are fed into a standalone calibration tool identifying the parameters of the vehicle drivetrain as well as the Luenberger feedback vector. Based on these data, a proper active damping control application is set-up and verified in various vehicle tests and to lead to the calibration finally to the application in several hybrid and electric vehicle series projects (e.g. Peugeot 3008 HYbrid4).

No abstract

This paper introduces the development and calibration process of a vehicle drivetrain observer used in hybrid and electric vehicles for active damping control (ADC) and for the improvement of the electric machine's rotor angle signal quality. This approach starts with creating an overall vehicle model that includes the electric machine, the transmission, side shafts, the tires and the vehicle body. For control engineering purposes, that multi-order-model is then reduced into a two-mass-oscillator which can be easily described in state-space form. Using this reduced drivetrain model and applying a Luenberger observer approach, not only the signal quality of both the instrumented rotor angle and the speed of the electric machine can be improved considerably but also the oscillation dynamics of this vehicle drivetrain can be estimated. If not compensated during vehicle operation, drivetrain oscillations might lead to increased drivetrain wear, NVH issues and limited ride comfort; therefore, the oscillation speed is very important in computing an active damping torque that is to compensate drivetrain oscillations. Calibration of the vehicle drivetrain observer is done using specific vehicle test data that are fed into a standalone calibration tool identifying the parameters of the vehicle drivetrain as well as the Luenberger feedback vector. Based on these data, a proper active damping control application is set-up and verified in various vehicle tests and to lead to the calibration finally to the application in several hybrid and electric vehicle series projects (e.g. Peugeot 3008 HYbrid4).