本文選題：純電動汽車　切入點：再生制動　出處：《重慶交通大學》2016年碩士論文　論文類型：學位論文

【摘要】：純電動汽車以其零排放、低噪音、不受石油匱乏影響等優(yōu)點日益受到全世界的廣泛關注,純電動汽車相關技術的研發(fā)也受到各大汽車公司、研究機構的高度重視。然而與傳統(tǒng)內燃機汽車相比,純電動汽車的續(xù)駛里程普遍受到電池容量的限制,無法完全滿足人們長距離的出行需求。得益于電機的發(fā)電特性,制動工況下,電動汽車可進行再生制動,將部分制動能量以電能的形式回收儲存,有效地提高整車能量使用率,延長續(xù)駛里程。制動力分配策略作為再生制動系統(tǒng)的重要組成部分,直接影響制動能量回收率的高低。模糊概念符合人類思維方式,基于模糊控制理論設計制動力分配策略可有效地實現(xiàn)對制動系統(tǒng)的控制。品質工學認為產品的品質是靠設計出來的,通過穩(wěn)健性設計能夠得到品質高、穩(wěn)健性優(yōu)異的產品。以再生制動模糊控制系統(tǒng)為開發(fā)對象,以提高能量回收率為試驗目的,對模糊控制系統(tǒng)進行穩(wěn)健性設計,以實現(xiàn)能量回收率的進一步提升。(1)基于制動相關法規(guī)和動力學模型,分析了再生制動影響因素,探討了三種典型再生制動策略的優(yōu)劣性。分析表明,再生制動控制策略設計過程中需要考慮電機性能、電池荷電狀態(tài)、路況以及制動強度的影響。(2)基于模糊控制理論,設計再生制動模糊控制系統(tǒng)。選擇車速、電池荷電狀態(tài)、制動強度為輸入變量,以再生制動力占比為控制目標,在保證制動穩(wěn)定性、保護電池的前提下,制定了模糊控制規(guī)則,并基于MATLAB模糊工具箱搭建了相應模型。(3)基于仿真軟件ADVISOR,檢驗模糊控制系統(tǒng)效果。對ADVISOR軟件進行二次開發(fā),基于MATLAB/Simulink軟件搭建再生制動模糊控制系統(tǒng),選擇日本1015工況、美國UDDS工況、美國紐約城市NYCC工況進行仿真實驗。試驗結果顯示再生制動模糊控制系統(tǒng)可有效地回收制動能量。(4)基于品質工學,優(yōu)化模糊控制模型。以模糊控制隸屬度函數(shù)形狀因子為優(yōu)化對象,對再生制動模糊控制系統(tǒng)進行性能改進。仿真試驗結果顯示,通過對隸屬度函數(shù)形狀的調整,三種工況下能量回收率取得了一定程度的提高,即控制系統(tǒng)的品質和穩(wěn)定性都取得了提高。在國家倡導推行“綠色出行、低碳生活”的背景下,適應電動汽車延長續(xù)駛里程的實際需求,在考慮制動穩(wěn)定性的前提下,建立了再生制動模糊控制模型,并通過品質工學對模糊控制模型進行了優(yōu)化改進,提出了性能穩(wěn)定、能量回收率高的再生制動控制系統(tǒng),為模糊控制與品質工學相結合的研究方式提供一定參考。
[Abstract]:Pure electric vehicles, with their advantages of zero emission, low noise, no oil shortage and so on, have attracted more and more attention all over the world. The research and development of pure electric vehicles related technologies have also been received by major automobile companies. However, compared with the traditional internal-combustion engine vehicles, the driving range of pure electric vehicles is generally limited by battery capacity, which can not fully meet the long distance travel needs of people. Under braking condition, the electric vehicle can be regenerated and stored in the form of electric energy, which can effectively improve the energy utilization rate of the whole vehicle. As an important part of regenerative braking system, braking force distribution strategy has a direct influence on braking energy recovery. The braking force distribution strategy based on fuzzy control theory can effectively control the braking system. Quality engineering believes that the quality of the product depends on the design, and high quality can be obtained through robust design. Taking regenerative braking fuzzy control system as the development object and improving the energy recovery rate as the experimental purpose, the robust design of the fuzzy control system is carried out. In order to realize the further improvement of energy recovery, based on the relevant regulations and dynamic models of braking, the influencing factors of regenerative braking are analyzed, and the advantages and disadvantages of three typical regenerative braking strategies are discussed. In the design of regenerative braking control strategy, the performance of motor, the charge state of battery, the influence of road condition and braking intensity should be considered. Based on fuzzy control theory, the fuzzy control system of regenerative braking should be designed. The braking strength is the input variable and the proportion of regenerative braking force is taken as the control target. On the premise of ensuring the braking stability and protecting the battery, the fuzzy control rules are formulated. The corresponding model is built based on MATLAB fuzzy toolbox. (3) based on the simulation software ADVISOR. the effect of fuzzy control system is tested. The secondary development of ADVISOR software is carried out, and the regenerative braking fuzzy control system is built based on MATLAB/Simulink software, and Japan 1015 working condition is selected. The simulation results show that the regenerative braking fuzzy control system can effectively recover the braking energy based on quality engineering. The fuzzy control model is optimized. Taking the shape factor of membership function of fuzzy control as the optimization object, the performance of regenerative braking fuzzy control system is improved. The simulation results show that, by adjusting the shape of membership function, The energy recovery rate has been improved to a certain extent under the three conditions, namely, the quality and stability of the control system have been improved. The fuzzy control model of regenerative braking is established under the premise of considering the braking stability to meet the actual demand of prolonging the driving range of electric vehicles. The fuzzy control model is optimized and improved by quality engineering, and the stability of performance is proposed. The regenerative braking control system with high energy recovery rate provides a certain reference for the research of the combination of fuzzy control and quality engineering.
【學位授予單位】：重慶交通大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：U469.72

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