發(fā)布時(shí)間：2018-06-10 19:32

  本文選題：機(jī)器車(chē) + 軟硬件設(shè)計(jì)��； 參考：《南昌航空大學(xué)》2013年碩士論文

【摘要】：目前，機(jī)器車(chē)(輪式機(jī)器人)是比較前沿的高新技術(shù)，涉及到電子技術(shù)人工智能自動(dòng)控制傳感器技術(shù)計(jì)算機(jī)技術(shù)等多個(gè)學(xué)科，也正朝著更高級(jí)更智能的方向發(fā)展。太陽(yáng)能電池是太陽(yáng)能機(jī)器車(chē)正常運(yùn)行的必要組成部分，能夠?yàn)闄C(jī)器車(chē)源源不斷的提供清潔能源。本文重點(diǎn)對(duì)基于GPS導(dǎo)航的太陽(yáng)能機(jī)器車(chē)的自主智能巡航控制系統(tǒng)、電機(jī)控制系統(tǒng)、DGPS/圖像匹配方法組合導(dǎo)航系統(tǒng)、太陽(yáng)能供電系統(tǒng)進(jìn)行研究。 論文分別介紹了機(jī)器車(chē)的硬件設(shè)計(jì)和軟件設(shè)計(jì)，硬件平臺(tái)采用意法半導(dǎo)體公司的STM32F103RBT6芯片作為核心處理器，并采用模塊化設(shè)計(jì)，包括自主智能巡航模塊、GPS導(dǎo)航模塊、電機(jī)控制模塊、液晶顯示和電源模塊。軟件部分主要是對(duì)機(jī)器車(chē)各個(gè)硬件模塊的驅(qū)動(dòng)程序進(jìn)行設(shè)計(jì)，并對(duì)DGPS/圖像匹配組合導(dǎo)航系統(tǒng)和太陽(yáng)能最大功率點(diǎn)跟蹤算法進(jìn)行分析仿真。 在DGPS/圖像匹配組合導(dǎo)航系統(tǒng)中，對(duì)位置差分、載波相位差分算法、組合導(dǎo)航原理進(jìn)行分析，并對(duì)SIFT算法進(jìn)行介紹和改進(jìn)，提高了其實(shí)時(shí)性。組合導(dǎo)航系統(tǒng)中采用卡爾曼濾波，評(píng)估導(dǎo)航參數(shù)的各種誤差狀態(tài)，并用誤差狀態(tài)評(píng)估值校正系統(tǒng)誤差，，提高導(dǎo)航精度。 能源管理是太陽(yáng)能機(jī)器車(chē)的關(guān)鍵技術(shù)之一，只有對(duì)能源分配進(jìn)行最優(yōu)化管理，才能最有效的發(fā)揮太陽(yáng)能能量的功效，因此對(duì)太陽(yáng)能最大功率點(diǎn)跟蹤(MPPT)算法的研究十分重要。本文在分析太陽(yáng)能電池?cái)?shù)學(xué)模型的基礎(chǔ)上采用干擾觀測(cè)法(PO)對(duì)太陽(yáng)能最大功率點(diǎn)跟蹤算法進(jìn)行仿真。干擾觀測(cè)算法簡(jiǎn)單，易于實(shí)現(xiàn)，被廣泛用于太陽(yáng)能最大功率點(diǎn)跟蹤研究上。這部分分別對(duì)太陽(yáng)能電池模塊最大功率點(diǎn)跟蹤模塊脈寬調(diào)制(PWM)模塊降壓式轉(zhuǎn)換器模塊分別進(jìn)行仿真，最后將這些模塊集成組合成太陽(yáng)能最大功率點(diǎn)跟蹤仿真模型，得到仿真結(jié)果并從結(jié)果中得出擾動(dòng)觀測(cè)法能準(zhǔn)確跟蹤太陽(yáng)能電池最大功率點(diǎn)的結(jié)論。
[Abstract]:At present, the machine car (wheeled robot) is a relatively cutting-edge high-tech, involving electronic technology? Artificial intelligence Auto-Control Sensor technology? Many subjects, such as computer technology, are also moving towards higher-level and more intelligent direction. Solar cells are an essential part of the normal operation of solar machine vehicles, which can provide clean energy for machine vehicles. This paper focuses on the autonomous intelligent cruise control system of solar machine vehicle based on GPS navigation, the integrated navigation system of DGPS/ image matching method of motor control system, The hardware design and software design of the machine vehicle are introduced in this paper. The hardware platform adopts STM32F103RBT6 chip of Italy Semiconductor Company as the core processor, and adopts the modular design. Includes autonomous intelligent cruise module GPS navigation module, motor control module, liquid crystal display and power module. In the software part, the driver of each hardware module of the machine vehicle is designed, and the DGPSimage matching integrated navigation system and the solar maximum power point tracking algorithm are analyzed and simulated. The position difference, carrier phase difference algorithm, integrated navigation principle are analyzed, and the sift algorithm is introduced and improved to improve its real-time performance. In the integrated navigation system, Kalman filter is used to evaluate the error state of navigation parameters, and the error state is used to correct the system error to improve the navigation accuracy. Energy management is one of the key technologies of solar machine vehicle. Only by optimizing the management of energy distribution can the most effective use of solar energy can be achieved. Therefore, it is very important to study the algorithm of maximum power point tracking (MPPTT) of solar energy. In this paper, based on the analysis of solar cell mathematical model, the maximum power point tracking algorithm of solar energy is simulated by means of interference observation method (POO). The interference observation algorithm is simple and easy to implement. It is widely used in the research of solar maximum power point tracking. This part of the solar cell module respectively? Maximum Power Point tracking Module? Pulse width Modulation (PWM) Modules? The step-down converter module is simulated separately. Finally, these modules are integrated into a solar maximum power point tracking simulation model. The simulation results and the conclusion that the perturbation observation method can accurately track the maximum power points of solar cells are obtained.
【學(xué)位授予單位】：南昌航空大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：TP242;P228.4

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本文編號(hào)：2004349