以模型為基礎之智能化車用感應馬達驅控系統研製及HiLS驗證技術研究

Abstract

本論文以模型為基礎(model-based)建立電動車馬達動力系統開發平台，將馬達控制演算法實施於dSPACE MicroautoboxII即時控制器開發平台上，進行馬達智慧化控制器設計，並實際驅控馬達，針對開發過程遇到之問題及步驟做討論；為提升開發平台安全及強健性，本論文導入小波轉換訊號分析技術針對開發過程中可預期之硬體損壞進行故障偵測，並以硬體測試資料驗證其可行性。 為提升行車安全及續航力，針對電動車輛之馬達再生煞車調配進行研究，以期能使用馬達達到防輪胎鎖死安全煞車之效果，並盡可能使用馬達再生煞車回收能源，藉以增加車輛續航力。本研究以滑模控制(Sliding mode control)理論進行輪胎滑差控制，與傳統防鎖死煞車系統進行回充能量比較，整合馬達再生煞車及液壓煞車，提供馬達煞車力之不足；而於多馬達動力系統之車輛，導入瞬時功率最小化策略(IPM)進行馬達系統動力分配最佳化，進一步提升馬達動力系統之效率，由不同情境下煞車之模擬結果顯示，此套控制技術使再生煞車時回收之能量有些微提升。

This thesis aims to construct an evaluation platform for model based electric vehicle powertrain system development. The electric motor controller algorithms will be implemented on the dSPACE MicroautoboxII real time prototyping controller to realize intelligent motor controller design, and through actually driving an electric motor, the developmental steps and soft/hardware trouble shooting will be closely examined. To increase the stability and robustness of the evaluation platform, the wavelet transformation method was used to analyze controller signals inorder to detect forseeable malfunction patterns caused by hardware failure, the methods will be validated through hardware experimentation. To improve the driving stability and the range of the electric vehicle, this thesis focuses on induction motor regenerative braking. Through regenerative braking, it can achieve the purpose of anti-lock braking and recycle more energy. This research proposes a wheel slip control based on sliding mode control algorithm and integrates motor regenerative braking and hydraulic braking system to provide more braking torque when insufficient. For electric vehicles with multiple traction motors, the instantaneous power minimization (IPM) strategy is adopted to deal with the torque distribution to enhance driving efficiency. Finally, MiL/HiL simulation presents the effects of the control strategy.