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基于隨機載荷功率譜的電動拖拉機復合能量系統(tǒng)研究
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國家重點研發(fā)計劃項目(2016YFD0701002)、拖拉機動力系統(tǒng)國家重點實驗室開放課題項目(SKT2016014)和河南省高??萍紕?chuàng)新人才支持計劃項目(18HASTIT026)


Electric Tractor Energy System and Management Strategy Research Based on Load Power Spectral Density
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    摘要:

    拖拉機重載作業(yè)模式下負載峰值功率和高頻功率存在較大隨機性,單一電源方案無法有效匹配電動拖拉機負載特性。通過分析拖拉機工況負載勢變量功率譜密度和電源放電特性,基于電動拖拉機通過主、輔電源對低、高頻功率分流的觀點,設計了采用DC-DC轉(zhuǎn)換器并聯(lián)超級電容器的18.5kW電動拖拉機復合電源方案,計算了系統(tǒng)參數(shù)。以平衡峰值功率和高頻載荷控制超級電容器功率流方向為目標,設計了基于邏輯門的雙DC-DC模式控制策略。根據(jù)負載時頻分析需求,構(gòu)建了基于Haar小波的雙通道濾波器組,設計了功率分配控制器。以標準正態(tài)分布白噪聲為基波,構(gòu)造拖拉機犁耕、旋耕載荷波動間的互譜函數(shù),建立了負載模擬模塊。采用CRUISE/Simulink API動態(tài)聯(lián)合仿真得出:基于功率分配控制的能量管理策略能夠?qū)恿﹄姵仉姽β室种圃谳d荷波動基頻附近,犁耕作業(yè)和旋耕作業(yè)下其電功率的截止頻率分別為2、7Hz,幅值符合正偏態(tài)分布;超級電容器平衡高頻載荷,其電功率符合標準正態(tài)分布。

    Abstract:

    When electric tractor working on heavy load model, such as plowing and rotary tillage, the peak power with high frequency of the working condition has more randomness. Energy systems of the electric tractor, which consists of single type of electric power source, e.g. batteries, may not effectively match the required power of dynamic load characteristic. Aimed at these problems, the electric tractor energy system and the management strategy were researched by the way based on the power spectral density of tractor load. By the analyses of electric drive train power flow, power spectral density of potential flow variables of tractor load and frequency characteristic in discharge process of common electric source, the feasibility of the way to separate the power flows with low frequency and high frequency via synergic electric power supply system was discussed. By mathematically building the constraint modelling of the endurance performance, power property, maximum using weight of tractor, steady and dynamic characteristic of load, the design method of energy systems with synergic electric power supply system in electric tractor was proposed. After that, the 18.5kW electric tractor energy system which was assembled by the parallel connection between batteries and super capacitors via DC-DC converter was designed. For the elimination of peak power with high frequency of battery and the direction control of the super capacitor power flow, the double DC-DC converter control strategy based on logic control was generated. For the requirement of time-frequency analysis, the power distribution controller of the management strategy was designed by using two-channel filter bank with Haar wavelet. By constructing the mutual spectral density function between Gaussian white noise and working load of the tractor on plowing and rotary tillage, the load-time wave used in the simulation was established. The simulation ran on the platform that the simulation model of tractor plowing and rotary tillage unit built on AVL CRUISE dynamically combined with the management strategy simulation model on Matlab/Simulink. And it can be found that the management strategy based on power spectral density can limit the frequency of the power flow transiting electric power the batteries of synergic electric power supply system on the fundamental frequency of working load. Under the plowing condition, the frequency of battery electric power was cut off at 2Hz. And under the rotary tillage condition, the frequency of battery electric power was cut off at 7Hz. The amplitudes of electric power flow conformed to positive skew distribution. The remainder of required power was provided by super capacitance. And the amplitudes of remaining electric power flow accorded with standard normal distribution. The research proposed can offer theory reference and technology support to other researchers whose working field would be related to electric tractor and energy management.

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劉孟楠,周志立,徐立友,趙靜慧,孟濤.基于隨機載荷功率譜的電動拖拉機復合能量系統(tǒng)研究[J].農(nóng)業(yè)機械學報,2018,49(2):358-366. LIU Mengnan, ZHOU Zhili, XU Liyou, ZHAO Jinghui, MENG Tao. Electric Tractor Energy System and Management Strategy Research Based on Load Power Spectral Density[J]. Transactions of the Chinese Society for Agricultural Machinery,2018,49(2):358-366.

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  • 收稿日期:2017-04-04
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  • 在線發(fā)布日期: 2018-02-10
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