An Improved Discharge Profile-Based DC-Link Capacitance Estimation for Traction Inverter in Electric Vehicle Applications
Xing Wei, Bo Yao, Yingzhou Peng, Yongchao Sun, Kai Wang, Huai Wang
Abstract
DC-link capacitor is an important part of traction inverters in electric vehicles (EVs), contributing to cost, size, and failure rate on a considerable scale. This paper proposes a non-invasive DC-link capacitance estimation method based on the capacitor discharge profile during the turning-off transition of a traction inverter. The proposed method relies on the existing control and measurement of the traction inverter without the need for software modifications and hardware updates. It minimizes the new risks introduced into the system operation because the estimation procedure is implemented after vehicles are parked. A novel correction solution is proposed to secure the estimation accuracy while also reducing the sampling requirements. Compared with conventional estimation methods, the proposed scheme outperforms in complexity and accuracy. The proof-of-concept experiments based on a scaled-down inverter prototype and a full-scale traction inverter for EV applications verify the feasibility of the proposed method.