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車(chē)輛混合動(dòng)力系統(tǒng)不確定性傳播與參數(shù)優(yōu)化
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國(guó)家自然科學(xué)基金資助項(xiàng)目（50905017）


Uncertainty Propagation and Parameter Optimization of Power System in Hybrid Electric Vehicle
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    摘要:

    根據(jù)混合動(dòng)力車(chē)輛的工作特性，對(duì)不確定下車(chē)輛混合動(dòng)力系統(tǒng)參數(shù)優(yōu)化的多學(xué)科設(shè)計(jì)優(yōu)化方法進(jìn)行研究,。采用蒙特卡羅仿真估計(jì)車(chē)輛混合動(dòng)力系統(tǒng)輸入?yún)?shù)的不確定性對(duì)系統(tǒng)性能的影響,；采用物理規(guī)劃法構(gòu)造系統(tǒng)性能目標(biāo)的綜合偏好函數(shù)和約束來(lái)滿足實(shí)際需求與設(shè)計(jì)偏好,；利用目標(biāo)分流法對(duì)車(chē)輛混合動(dòng)力系統(tǒng)的參數(shù)優(yōu)化問(wèn)題進(jìn)行層次分解及協(xié)同優(yōu)化,。最終方案不僅使混合動(dòng)力系統(tǒng)的功率匹配更加滿足設(shè)計(jì)偏好，還使系統(tǒng)的設(shè)計(jì)參數(shù)達(dá)到最優(yōu)配置,。

    Abstract:

    According to the working characteristic of hybrid electric vehicle (HEV) in different conditions, the multidisciplinary design optimization (MDO) method in parameter optimization of power system of HEV under uncertainty was studied. To estimate the impact of uncertain input parameters on objectives of drive power system by performing the Monte Carlo simulation. The aggregate preference function of objectives and corresponding constraint equation were constructed to satisfy the designers’ preference and engineering design. The power system parameters were optimized by using analytical target cascading (ATC) method which could hierarchically decompose and collaboratively optimize the system. The results showed that the values of vehicle’s performance and the power system design could be optimized currently.

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王婷婷,陳瀟凱,林逸.車(chē)輛混合動(dòng)力系統(tǒng)不確定性傳播與參數(shù)優(yōu)化[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2013,44(8):21-26. Wang Tingting, Chen Xiaokai,Lin Yi. Uncertainty Propagation and Parameter Optimization of Power System in Hybrid Electric Vehicle[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(8):21-26.

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  • 在線發(fā)布日期: 2013-07-19
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