本文旨在探討循跡防滑控制方法,應用於全時四輪驅動之電動車。當車輛行駛在濕滑路面時,透過四輪驅動系統,能妥善的調配各驅動輪之扭力輸出。因此,全時四輪驅動車具有較好之行駛操控性及穩定性。循跡防滑控制在四輪驅動系統中,藉由打滑比之控制,決定如何調控扭力。在過去,有許多文獻在以汽油引擎車為標的,提出打滑比控制之方法。 相較於汽油引擎車,循跡滑控制方法在電動車上,可以有進一步表現。此是由於電動車使用馬達作為動力來源,而馬達相較於引擎,扭力之控制響應較為精準。因此,控制時輪胎與路面間之摩擦力,較能被即時推算取得,而循跡防滑控制可藉即時摩擦力估測,達到最佳化之打滑比控制。 另一項關鍵技術為車速估測。絕對車速之值對於計算打滑比相當重要,但在全時四輪驅動車上,車速相當難以取得。考量成本以及可靠性,本研究採用加速規取得動態資訊。接著,本研究運用適應性卡爾曼濾波以及多感測器資料融合於系統,提昇速度估測之準度。
This paper describes a Traction Control System (TCS) for an All-Wheel-Drive (AWD) electric vehicle. When a vehicle passes slippery road surface, the AWD system can appropriately regulate torque output of each wheel. Therefore, the AWD car has better maneuverability and stability. The torque regulation methods are based on the TCS, which control slip ratio of wheels. In the past, many slip ratio control methods have been proposed for gasoline engine vehicle. Comparing to gasoline engine vehicles, the TCS can be more effective on electric vehicles. The power source of electric vehicle is motor, whose torque response is more precise than gasoline engine system. Therefore, the real-time friction force between tire and road can be derived. Therefore, the TCS determines optimal slip ratio with the friction force estimation. Another key technology is speed estimator. Absolute vehicle speed is essential to calculate slip ratio, but it is difficult to get the speed on AWD vehicles. Considering cost and reliability, this study uses a accelerometer to obtain dynamic information. Furthermore, adaptive filter and multi sensor data fusion are added in order to improve the estimation accuracy.