電動車同步磁阻馬達驅動系統之開發及其與電網/微電網之互聯操作

DEVELOPMENT OF AN ELECTRIC VEHICLE SYNCHRONOUS RELUCTANCE MOTOR DRIVE AND ITS INTERCONNECTED OPERATIONS TO GRID AND MICROGRID

甘尼瑟(Kumar, Ganisetti Vijay)

指導教授 ： 廖聰明

國立清華大學/電機資訊學院/電機工程學系所/博士(2021年)

摘要

本論文旨在開發一電動車同步磁阻馬達驅動系統，並從事其與電網及微電網間之雙向操控。首先，建立一標準同步磁阻馬達驅動系統，其考慮槽齒效應之電流控制機構及速度控制機構均妥以設計。同時以所提適應換相機構，自動調整換相時刻，獲得馬達總損失最小化。為增進廣速度範圍之驅動性能，以一單臂雙向升降壓直流/直流轉換器作為蓄電池及馬達變頻器間之介面，建立與速度關聯之直流鏈電壓。馬達再生煞車回收之電能，亦可成功回存至蓄電池。
接者，建立一具廣速度及負載範圍之無位置感測電動車同步磁阻馬達驅動系統。為解決既有方法所面臨之關鍵問題，先探究在直軸及交軸注入下，注入電流與槽齒諧波電流準位之影響。再據以提出交軸高頻注入機構，考慮與速度及/或負載關聯之槽齒漣波電流，採變頻注入機制。感測之直軸電流，經處理獲得穩定且準確之估測轉子位置。此外，亦加入強健速度及位置估測控制，增強無位置感測馬達之控制性能。
最後，本論文從事所建馬達驅動系統之車輛至電網及車輛至微電網之雙向操控。於閒置狀態，僅需外加低通濾波器，應用既有之介面轉換器及馬達變頻器，即可達成所安排之操作。車載蓄電池可由電網充電，而具良好入電品質。反之於車輛至電網模式，蓄電池可回送功率至電網。三相及單相聯網操控皆可，甚至在單相下，馬達之線圈電感可取代外加電感。相同電路組成，亦可從事微電網至車輛及車輛至微電網操作，於此以一風力開關式磁阻發電機為主之微電網為之。藉所安排之控制，可成功執行電動車於微電網之移動式儲能應用，有效利用再生能源。

關鍵字

同步磁阻馬達 ； 電動車 ； 蓄電池 ； 換相調整 ； 損失最小化 ； 電流控制 ； 速度控制 ； 再生煞車 ； 無位置感測控制 ； 高頻信號注入 ； 電網至車輛 ； 車輛至電網 ； 微電網至車輛 ； 車輛至微電網

並列摘要

This dissertation presents the development of an electric vehicle (EV) synchronous reluctance motor (SynRM) drive and its bidirectional operations to grid and microgrid. First, a standard synchronous reluctance motor drive is established with proper current control considering inherent slotting effects and speed control. An adaptive commutation scheme (ACS) is developed to automatically set the commutation instant for achieving the motor total loss minimization. To enhance the driving performance over wide speed range, a bi-directional one-leg boost-buck DC/DC converter is used as an interface between battery and motor-drive inverter to establish the speed dependent varied DC-link voltage. The regenerative braking energy can also be successfully recovered to the battery.
Second, a position sensorless EV SynRM drive having wide speed and load ranges is developed. To solve the key problems encountered by existing approaches, the comparative effects of biased injected current and slotting harmonic current levels for d- and q-axis injections are explored. Then the high-frequency injection (HFI) scheme based on q-axis injection is proposed. The changed-frequency injection is adopted considering the effects of speed/load dependent slotting ripple current. The detected d-axis current is processed to yield stable and accurate estimated rotor position. The robust observed speed and position controllers are added to enhance the sensorless control performance.
Finally, this dissertation presents the vehicle-to-grid (V2G) and vehicle-to-microgrid (V2M) bidirectional operations of the developed EV SynRM drive. In idle condition, the embedded interface converter and inverter of motor drive are arranged to perform the G2V/V2G operations. Only the low-pass filters are needed to add externally. Through proper controls, the on-board battery can be charged from mains in G2V mode with good line drawn power quality. Conversely in V2G operation, the battery can send power back to the utility grid. Three-phase and single-phase grid connected operations are all applicable. For the single-phase case, the armature windings are further utilized to replace the externally added inductor. Moreover, through the same schematics, the M2V/V2M operations can also be conducted. A wind switched-reluctance generator (SRG) based microgrid is employed here. The EV movable energy storage application to microgrid is successfully operated via the arranged controls to effectively utilize the renewable sources.

並列關鍵字

Synchronous reluctance motor ； electric vehicle ； battery ； commutation tuning ； loss minimization ； current control ； speed control ； regenerative braking ； position sensorless control ； high-frequency signal injection ； grid-to-vehicle ； vehicle-to-grid ； grid-to-microgrid ； microgrid-to-grid

參考文獻

A. Electric Vehicles

[1] Shumei Cui, Shouliang Han, and C. C. Chan, “Overview of multi-machine drive systems for electric and hybrid electric vehicles,” in Proc. IEEE ITEC Asia-Pacific, 2014, pp. 1-6.

[2] G. Wu, K. Boriboonsomsin, and M. J. Barth, “Development and evaluation of an intelligent energy-management strategy for plug-in hybrid electric vehicles,” IEEE Trans. Syst., vol. 15, no. 3, pp. 1091-1100, 2014.

[3] C. C. Chan, A. Bouscayrol, and K. Chen “Electric, hybrid, and fuel-cell vehicles: architectures and modeling,” IEEE Trans. Veh. Technol., vol. 59, no. 2, pp. 589-598, 2010.

[4] S. G. Wirasingha and A. Emadi, “Classification and review of control strategies for plug-in hybrid electric vehicles,” IEEE Trans. Veh. Technol., vol. 60, no. 1, pp. 111-122, 2011.