電動車主動式煞車回充系統之 建模與性能評估
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2014
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本研究主要在以MATLAB/Simulink研發一可用於電動車的煞車回充系統，以期達到最佳能量回收之目標，本系統包含高功率馬達、機械煞車、鋰電池等部分。將各車輛負載資訊輸入至車輛動態分析模組後，計算出車輛動態資訊並將其送至各系統進行最佳煞車控制，而為進行最佳煞車控制，依現有高功率馬達系統建立主動與被動式煞車模型，並以規則庫控制將煞車回充能量最佳化，分析回充能量結果，最後將最佳煞車控制模型進行驗證及差異修正。主動式煞車定義為最佳化再生煞車後，以機械煞車補足不足之部分；被動式則主要以機械煞車進行煞車，剩餘之部分再根據不足的部分由再生煞車補足。為精確模擬實際行車時之煞車能量，將物理模型燒錄至底盤動力計進行煞車能量測試，實測之煞車能量為13828 kJ，而模擬之煞車能量則為13670 kJ，兩者差距只占實際煞車能量的1.14 %，因此模擬與實測結果十分接近，代表此物理模型可準確模擬實際煞車回充狀況。而本研究為能比較出煞車車速及煞車時間對回充能量的影響，訂出以3種不同車速(30 km/h、60 km/h、90 km/h)在三種不同煞車時間(10秒、15秒、20秒)內進行煞車之行車型態。為模擬車輛在正常行駛狀態之回充能量，本研究選定兩種行車型態(FTP-75與ECE-40)做回充能量測試，模擬結果顯示，當煞車時間越短及以越高車速進行煞車時，能使煞車回充系統回收到較多的能量。由最佳能量回收效益可知，主動式煞車之能量回收為總能量消耗之 4.38 %，被動式則為0.24 %，因此主動式煞車之能量回收效益約為被動式煞車之18.25倍左右。
This thesis mainly evaluates a brake regenerative system in electric vehicles (EVs) by using the Matlab/Simulink software package in order to recovering the optimal brake energy. The system consists of a high-power motor, a mechanical brake, lithium battery etc.. After the vehicle load information is sent to the vehicle dynamics model, the optimal brake control is conducted. We modeled the active and passive braking model based on the high-power motor dynamics. The rule-based control was used for the energy optimization. The regenerative energy was analyzed, and the optimal control model was verified and then modified. The active brake system activates the regenerative brake first, and then the mechanical brake compensates the rest of the energy. The passive energy uses the mechanical brake for the main brake power, while the regenerative brake compensates the rest. To accurately simulate the braking energy while driving, the real brake energy tested on the chassis dynamometer was compared to the model. The test brake energy was 13828 kJ, while the simulated one was 13670 kJ. The difference is only 1.14%, which indicates that the physical model can precisely emulated the vehicle brake operation. In order to comparing the effect of vehicle speed to the brake energy, three initial speeds (30 km/h, 60 km/h, and 90 km/h) and three braking time (10 sec., 20 sec., and 30 sec.) are set to be the braking conditions. Meanwhile, to simulate the normal driving, two driving cycles: FTP-75 and ECE40 are selected for the evaluation of brake regeneration. Simulation results show that with shorter braking time and higher initial speed, the regenerative brake recovers more energy. From the optimal energy recovery, the active brake system can recover 4.38% of total consumed energy, while the passive brake system recovers 0.24%. The active brake system recovers 18.25 times energy than the passive brake system.
This thesis mainly evaluates a brake regenerative system in electric vehicles (EVs) by using the Matlab/Simulink software package in order to recovering the optimal brake energy. The system consists of a high-power motor, a mechanical brake, lithium battery etc.. After the vehicle load information is sent to the vehicle dynamics model, the optimal brake control is conducted. We modeled the active and passive braking model based on the high-power motor dynamics. The rule-based control was used for the energy optimization. The regenerative energy was analyzed, and the optimal control model was verified and then modified. The active brake system activates the regenerative brake first, and then the mechanical brake compensates the rest of the energy. The passive energy uses the mechanical brake for the main brake power, while the regenerative brake compensates the rest. To accurately simulate the braking energy while driving, the real brake energy tested on the chassis dynamometer was compared to the model. The test brake energy was 13828 kJ, while the simulated one was 13670 kJ. The difference is only 1.14%, which indicates that the physical model can precisely emulated the vehicle brake operation. In order to comparing the effect of vehicle speed to the brake energy, three initial speeds (30 km/h, 60 km/h, and 90 km/h) and three braking time (10 sec., 20 sec., and 30 sec.) are set to be the braking conditions. Meanwhile, to simulate the normal driving, two driving cycles: FTP-75 and ECE40 are selected for the evaluation of brake regeneration. Simulation results show that with shorter braking time and higher initial speed, the regenerative brake recovers more energy. From the optimal energy recovery, the active brake system can recover 4.38% of total consumed energy, while the passive brake system recovers 0.24%. The active brake system recovers 18.25 times energy than the passive brake system.
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Keywords
煞車回充, 最佳化, 電動車, regenerative braking, optimization, electric vehicle