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系統識別號 U0026-2811201920344300
論文名稱(中文) 中度油電混合車之適應性遙測動力分配策略
論文名稱(英文) Adaptive Telemetry Power Split Strategy for Mild Hybrid Electric Vehicle
校院名稱 成功大學
系所名稱(中) 機械工程學系
系所名稱(英) Department of Mechanical Engineering
學年度 108
學期 1
出版年 108
研究生(中文) 謝秉學
研究生(英文) Ping-Hsueh Hsieh
學號 N16060036
學位類別 碩士
語文別 中文
論文頁數 122頁
口試委員 指導教授-蔡南全
口試委員-黃運琳
口試委員-潘敏俊
中文關鍵字 油電混合車  能量管理策略  適應性遙測等效油耗最小策略  前-後視縱向車體模型 
英文關鍵字 Hybrid Electric Vehicle (HEV)  Forward-backward Facing Longitudinal Vehicle Model  Energy Management Strategy (EMS)  Adaptive Telemetry Equivalent Consumption Minimization Strategy (AT-ECMS) 
學科別分類
中文摘要 本論文針對配置曲軸式集成起動發電機(Crankshaft-mounted Integrated Starter Generator, C-ISG)之中度油電混合車(Hybrid Electric Vehicle, HEV)提出能量管理策略(Energy Management Strategy, EMS),使用適應性遙測等效油耗最小策略(Adaptive Telemetry Equivalent Consumption Minimization Strategy, AT-ECMS),將引擎之燃油與電池之化學能整合為等效油耗,藉由最佳化等效油耗求出最佳的引擎以與ISG輸出扭矩。
本論文之目標在於: 行駛於未知行車型態下(i).減少燃油消耗; (ii).維持電池電量。 為了達到上述目標,本論文提出: 利用終端消耗能量之假設條件,配合過去以及現有的行車型態資訊更新AT-ECMS中的等效因子,使其能兼顧維持電池電量(Charge-retaining)任務並有效地使用電池,優化油耗表現。 較於其他現行能量管理策略,AT-ECMS特點有三: (i).無須計算離線最佳化參數、(ii).儲存較少的能量策略參數、(iii).無須估測未來行車型態(車速或是加速度)。
為了驗證本論文提出之能量管理策略之效用,本論文使用車輛模擬軟體ADVISOR(ADvanced VehIcle SimulatOR)之車體參數與MATLAB/Simulink建立之前-後視縱向車體模型,針對提出之能量管理策略(AT-ECMS)進行模擬分析。
由模擬之結果得知: 本論文提出之AT-ECMS相較於動態規劃(最佳解)之結果,於油耗方面,在市區、郊區與高速公路之行車型態最高分別僅有1.06%、0.4%與0.16%之差異。 此外,電池電量亦可維持於55%附近,驗證了本論文提出之能量管理策略有卓越的成效。
英文摘要 In this thesis, an innovative Energy Management Strategy (EMS) for mild Hybrid Electric Vehicle (HEV) equipped with Crankshaft-mounted Integrated Starter Generator (C-ISG) is proposed. With the major aim at reducing fuel consumption and retaining battery State of Charge (SOC) level, Adaptive Telemetry Equivalent Consumption Minimization Strategy (AT-ECMS) is established. AT-ECMS is emphasized to work under unknown driving conditions without explicit prediction of driving conditions and heavy time-consuming offline computation load. In contrast to most current EMS, AT-ECMS has relatively computational-friendly structure, therefore it can be realized in real-world driving conditions effortlessly. To evaluate the performance of AT-ECMS, forward-backward facing longitudinal vehicle model and AT-ECMS are developed and verified under MATLAB/Simulink environment. According to the simulation results, better fuel economy under unknown driving condition can be achieved by the proposed AT-ECMS. Compared to the optimal result via dynamic programming, only a minor degree of discrepancy in fuel economy is found.
論文目次 摘要 I
誌謝 VII
目錄 VIII
表目錄 XI
圖目錄 XII
符號與簡寫表 XV
第一章 緒論 1
1.1 前言 1
1.2 研究動機與目的 3
1.3 文獻回顧 5
1.4 論文架構 7
第二章 縱向車體模型 9
2.1 前視模型(Forward-Facing Model) 14
2.1.1 動力傳動系統模型(Power-train Model) 15
2.1.2 輪胎模型(Wheel/Tire Model) 19
2.1.3 縱向車體模型(Longitudinal Vehicle Model) 25
2.2 後視模型(Backward-Facing Model) 27
2.2.1 引擎模型(Engine Model) 29
2.2.2 排汙後處理模型(Emission Aftertreatment Model) 32
2.2.3 一體式起動發電機模型(ISG Model) 39
2.2.4 電池模型(Battery Model) 41
第三章 問題敘述及現有方法討論 44
3.1 針對油電混合車之能量管理策略的問題敘述 45
3.2 動態規劃(Dynamic Programming) 48
3.3 等效油耗最小策略 53
3.3.1 最大化原理與ECMS之間的關係 54
3.3.2 最佳性原理與ECMS之間的關係 57
3.4 適應性等效油耗最小策略 61
第四章 控制策略設計及模擬 75
4.1 適應性遙測等效油耗最小策略 75
4.1.1 等效因子上下限 77
4.1.2 機率因子計算 79
4.1.3 參數更新 80
4.1.4 終端能量估測 81
4.1.5 確保電池電量之上下限 83
4.1.6 適應性遙測等效油耗最小策略 84
4.2 模擬結果 84
4.2.1 車體參數 86
4.2.2 模擬步驟 86
4.2.3 AT-ECMS等效因子更新律使用參數 88
4.2.4 油耗經濟性與終端電池電量之關係 91
4.2.5 ECMS與P-ECMS之關係 101
4.2.6 AT-ECMS等效因子以及機率因子對SOC軌跡之關係 103
第五章 結論及未來展望 109
5.1 結論 109
5.2 未來展望 111
參考文獻 113
附錄A 最佳控制問題之一階必要條件 120
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