【摘要】：隨著信息技術(shù)的發(fā)展，嵌入式系統(tǒng)被廣泛的應(yīng)用于日常生活的方方面面，嵌入式系統(tǒng)在汽車電子、網(wǎng)絡(luò)設(shè)備、航空航天、微控制、消費電子、工業(yè)控制、安全系統(tǒng)等領(lǐng)域方興未艾，尤其是在汽車電子領(lǐng)域已成為汽車整車不可分割的一部分。 由于我國國民經(jīng)濟的發(fā)展和人民生活水平的日益提高，汽車開始走進(jìn)千家萬戶，與此同時帶來的環(huán)境問題也日益突出，電動汽車以其零排放、低噪音的優(yōu)點越來越受到人們的青睞。電源管理系統(tǒng)作為電動汽車的關(guān)鍵部分，也越來越受到各個國家的重視。 本文重點研究了電動汽車電源管理系統(tǒng)的特點和未來的發(fā)展方向，設(shè)計了一種基于ARM9的嵌入式電源管理系統(tǒng)。由于傳統(tǒng)的電源管理系統(tǒng)對電池組剩余電量測量時受外界影響因素很大，使我們對系統(tǒng)建立具體模型很困難，為此本文采用了神經(jīng)網(wǎng)絡(luò)算法對電池組剩余電量進(jìn)行預(yù)測，神經(jīng)網(wǎng)絡(luò)算法無需建立復(fù)雜的電池模型，，但神經(jīng)網(wǎng)絡(luò)算法需要很多組測量值對網(wǎng)絡(luò)進(jìn)行訓(xùn)練，需要很長的訓(xùn)練時間，同時網(wǎng)絡(luò)易陷入局部極值，為了克服這些缺點，采用了自適應(yīng)遺傳算法優(yōu)化后的神經(jīng)網(wǎng)絡(luò)算法，通過仿真實驗，證實此算法具有很好的穩(wěn)定性和控制精度。使用三星公司的ARM9內(nèi)核芯片S3C2410作為系統(tǒng)的主控制器，進(jìn)行了最小系統(tǒng)設(shè)計，同時設(shè)計了數(shù)據(jù)采集電路和熱管理電路，并進(jìn)行了相應(yīng)的軟件開發(fā)。最后在實驗室環(huán)境中進(jìn)行運行調(diào)試，使系統(tǒng)具有了良好的穩(wěn)定性。
[Abstract]:With the development of information technology, embedded systems are widely used in all aspects of daily life. Embedded systems are used in automotive electronics, network equipment, aerospace, micro-control, consumer electronics, industrial control, and so on. Safety systems and other fields are in the ascendant, especially in the field of automotive electronics has become an integral part of the vehicle. As a result of the development of our country's national economy and the increasing living standard of the people, cars begin to enter thousands of households, and at the same time, the environmental problems brought about by them are becoming more and more prominent. With the zero emission of electric vehicles, The advantages of low noise are getting more and more popular. As a key part of electric vehicle, power management system has been paid more and more attention by many countries. This paper focuses on the characteristics and future development of electric vehicle power management system, and designs an embedded power management system based on ARM9. Because the traditional power management system is greatly influenced by the external factors, it is very difficult for us to establish the specific model of the system. Therefore, the neural network algorithm is used to predict the residual power of the battery pack, which makes it very difficult for us to establish the specific model of the system. The neural network algorithm does not need to establish the complex battery model, but the neural network algorithm needs a lot of measured values to train the network, and needs a long training time. At the same time, the network is easy to fall into the local extremum, in order to overcome these shortcomings. The neural network algorithm optimized by adaptive genetic algorithm is adopted. The simulation results show that the algorithm has good stability and control precision. Using the ARM9 core chip S3C2410 of Samsung Company as the main controller of the system, the minimum system design is carried out. At the same time, the data acquisition circuit and the thermal management circuit are designed, and the corresponding software development is carried out. Finally, running and debugging in the laboratory environment, the system has a good stability.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：TP368.1;TP315

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