本文選題：純電動(dòng)汽車(chē)　切入點(diǎn)：再生制動(dòng)　出處：《重慶交通大學(xué)》2016年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：純電動(dòng)汽車(chē)以其零排放、低噪音、不受石油匱乏影響等優(yōu)點(diǎn)日益受到全世界的廣泛關(guān)注,純電動(dòng)汽車(chē)相關(guān)技術(shù)的研發(fā)也受到各大汽車(chē)公司、研究機(jī)構(gòu)的高度重視。然而與傳統(tǒng)內(nèi)燃機(jī)汽車(chē)相比,純電動(dòng)汽車(chē)的續(xù)駛里程普遍受到電池容量的限制,無(wú)法完全滿足人們長(zhǎng)距離的出行需求。得益于電機(jī)的發(fā)電特性,制動(dòng)工況下,電動(dòng)汽車(chē)可進(jìn)行再生制動(dòng),將部分制動(dòng)能量以電能的形式回收儲(chǔ)存,有效地提高整車(chē)能量使用率,延長(zhǎng)續(xù)駛里程。制動(dòng)力分配策略作為再生制動(dòng)系統(tǒng)的重要組成部分,直接影響制動(dòng)能量回收率的高低。模糊概念符合人類(lèi)思維方式,基于模糊控制理論設(shè)計(jì)制動(dòng)力分配策略可有效地實(shí)現(xiàn)對(duì)制動(dòng)系統(tǒng)的控制。品質(zhì)工學(xué)認(rèn)為產(chǎn)品的品質(zhì)是靠設(shè)計(jì)出來(lái)的,通過(guò)穩(wěn)健性設(shè)計(jì)能夠得到品質(zhì)高、穩(wěn)健性?xún)?yōu)異的產(chǎn)品。以再生制動(dòng)模糊控制系統(tǒng)為開(kāi)發(fā)對(duì)象,以提高能量回收率為試驗(yàn)?zāi)康?對(duì)模糊控制系統(tǒng)進(jìn)行穩(wěn)健性設(shè)計(jì),以實(shí)現(xiàn)能量回收率的進(jìn)一步提升。(1)基于制動(dòng)相關(guān)法規(guī)和動(dòng)力學(xué)模型,分析了再生制動(dòng)影響因素,探討了三種典型再生制動(dòng)策略的優(yōu)劣性。分析表明,再生制動(dòng)控制策略設(shè)計(jì)過(guò)程中需要考慮電機(jī)性能、電池荷電狀態(tài)、路況以及制動(dòng)強(qiáng)度的影響。(2)基于模糊控制理論,設(shè)計(jì)再生制動(dòng)模糊控制系統(tǒng)。選擇車(chē)速、電池荷電狀態(tài)、制動(dòng)強(qiáng)度為輸入變量,以再生制動(dòng)力占比為控制目標(biāo),在保證制動(dòng)穩(wěn)定性、保護(hù)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(yīng)模型。(3)基于仿真軟件ADVISOR,檢驗(yàn)?zāi)：刂葡到y(tǒng)效果。對(duì)ADVISOR軟件進(jìn)行二次開(kāi)發(fā),基于MATLAB/Simulink軟件搭建再生制動(dòng)模糊控制系統(tǒng),選擇日本1015工況、美國(guó)UDDS工況、美國(guó)紐約城市NYCC工況進(jìn)行仿真實(shí)驗(yàn)。試驗(yàn)結(jié)果顯示再生制動(dòng)模糊控制系統(tǒng)可有效地回收制動(dòng)能量。(4)基于品質(zhì)工學(xué),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(duì)象,對(duì)再生制動(dòng)模糊控制系統(tǒng)進(jìn)行性能改進(jìn)。仿真試驗(yàn)結(jié)果顯示,通過(guò)對(duì)隸屬度函數(shù)形狀的調(diào)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(zhì)和穩(wěn)定性都取得了提高。在國(guó)家倡導(dǎo)推行“綠色出行、低碳生活”的背景下,適應(yīng)電動(dòng)汽車(chē)延長(zhǎng)續(xù)駛里程的實(shí)際需求,在考慮制動(dòng)穩(wěn)定性的前提下,建立了再生制動(dòng)模糊控制模型,并通過(guò)品質(zhì)工學(xué)對(duì)模糊控制模型進(jìn)行了優(yōu)化改進(jìn),提出了性能穩(wěn)定、能量回收率高的再生制動(dòng)控制系統(tǒng),為模糊控制與品質(zhì)工學(xué)相結(jié)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(xué)位授予單位】：重慶交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：U469.72

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