【作者】 刘亮；

【导师】 袁小芳；

【作者基本信息】 湖南大学 ， 控制科学与工程， 2019， 硕士

【摘要】 电动汽车作为解决汽车尾气排放问题的一种有效方式,受到了全世界各国越来越广泛的关注。相比于传统电动汽车,分布式驱动电动汽车(Distributed Drive Electric Vehicles,DDEV)不仅具有转矩精确可控,响应速度快等优势,而且还具有更多的自由度,使得电动汽车控制变得更加灵活。基于DDEV的这些特点,使得DDEV的动力学控制成为这些年来学者的研究重点。本文以DDEV的纵向运行为研究目标,针对其纵向运行中存在工况切换不稳定和多工况条件下难以实现最优滑移率控制问题展开了以下研究:1、根据DDEV的纵向物理特性及动力学特性,分别建立了DDEV的二自由度整车动力学模型、八自由度整车动力学模型、轮胎模型、车轮动力学模型以及DDEV纵向稳定性运行的判定条件。2、为了解决DDEV纵向运行中工况切换时造成运行不稳定问题,本文提出了一种基于多模型预测控制软切换控制方法。首先将DDEV纵向运行工况划分为3种,对其分别建立相对应的动力学模型和参考模型,对每种工况设计了子模型预测控制器。然后通过改进的递归贝叶斯方法计算各子模型控制器的权值系数。最后通过子模型预测控制器输出与各子模型权值系数的加权叠加得到多模型预测控制器的输出,从而实现了DDEV纵向运行时工况的平滑切换。通过与传统多模型预测控制硬切换控制方法的仿真结果比较,验证了所提出的控制策略的有效性。3、为了解决DDEV纵向多工况运行条件下难以实现最优滑移率控制问题,本文提出了一种基于多模型预测控制的DDEV最优滑移率控制策略。首先将DDEV纵向运行工况划分为15种典型工况,分别对每种典型工况建立了子模型以及针对每一种典型工况子模型设计了基于模型预测控制的最优化滑移率控制器。然后通过工况识别器计算DDEV当前运行工况与15种典型工况之间匹配系数。最后,多模型预测控制器输出由各子模型预测控制器输出与识别器输出加权求和得到。从而实现了DDEV纵向运行的多工况下的最优滑移率控制。更多还原

【Abstract】 As an effective way to solve the problem of vehicle exhaust emissions,electric vehicles have attracted more and more attention from all over the world.Compared with traditional electric vehicles,distributed drive electric vehicles(DDEV)not only have the advantages of precise torque control and quick response,but also has more degrees of freedom,which makes the control of electric vehicles more flexible.Based on these characteristics of DDEV,dynamic control of DDEV has become the research focus of researchers in these years.In this paper,the longitudinal operation of DDEV is taken as the research target,and the following research is carried out for the problem of working condition switching unstable and difficult to achieve optimal slip rate control in its longitudinal operation.1、According to the longitudinal physical and dynamic characteristics of DDEV,two-degree-of-freedom vehicle dynamics model,eight-degree-of-freedom vehicle dynamics model,tire model,wheel dynamics model and judging conditions of DDEV longitudinal stability operation are established respectively.2、In order to solve the unstable operation problem caused by the switching of the working condition in the longitudinal operation of the DDEV,a soft-switching control method based on multi-model predictive control is proposed in this paper.Firstly,the DDEV longitudinal operation conditions are divided into three typical operating modes,and the corresponding dynamic model and reference model are established respectively.The sub-model predictive controller is designed for each working condition.Then the weight of each sub-model controller is calculated by improved recursive Bayesian method.Finally,the output of the multi-model predictive controller is obtained by weighting the output of the sub-model predictive controller and the weights of each sub-model,thus the smooth switching of the DDEV longitudinal operation conditions is realized.The effectiveness of the proposed control strategy is verified by comparison with the simulation results of traditional multi-model hard switching.3、In order to solve the problem that it is difficult to achieve optimal slip rate control under longitudinal multi-operating conditions of DDEV.An optimal slip rate control strategy based on multi-model predictive control for DDEV is proposed in this paper.Firstly,the DDEV longitudinal operation conditions are divided into 15 typical operating modes,and sub-models were established for each typical operating condition.An optimal slip rate controller based on model predictive control is designed for each typical sub-model.Then,the matching coefficient between the current operating condition of DDEV and 15 typical working conditions is calculated by the condition identifier.Finally,the output of the multi-model predictive controller is obtained by weighted summation of the output of each sub-model predictive controller and the output of the identifier.Thus,the optimal slip rate control of DDEV under multi-operating conditions is realized.更多还原