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分布式电动汽车驱动力分配控制方法研究1. 引言今天，随着科技的不断发展和社会的进步，电动汽车已经成为一种越来越受欢迎的交通工具。
与传统内燃机汽车相比，电动汽车具有环保、节能、安静等优势，受到越来越多的消费者和政府的关注和支持。
在电动汽车的发展过程中，分布式驱动力分配控制方法成为了一个关键的研究领域。
它不仅关乎电动汽车的性能和安全，也对电动汽车的智能化和自动化技术提出了挑战和机遇。
2. 分布式电动汽车驱动力分配控制方法的基本概念分布式电动汽车驱动力分配控制方法是指通过控制电动汽车不同轮子上的驱动力分配，实现汽车的动力输出、转向和稳定控制。
这种方法可以根据不同路面情况和行驶状态，合理地分配驱动力，提高汽车的稳定性和安全性，最大限度地发挥电动汽车的性能优势。
分布式电动汽车驱动力分配控制方法一直以来都是电动汽车研究和开发的重要方向，涉及到机械、控制、电气、信息等多个领域。
3. 相关技术和方法在分布式电动汽车驱动力分配控制方法的研究中，有许多相关的技术和方法被提出并得到了广泛应用。
基于车辆动力学模型的控制方法，采用传感器和实时反馈系统的辅助控制方法，以及结合车辆稳定性控制的整车动态控制方法等等。
这些方法在不同情况下可以实现不同的优势，有助于提高电动汽车的动态性能和安全性能。
4. 分布式电动汽车驱动力分配控制方法的挑战与发展然而，分布式电动汽车驱动力分配控制方法也面临着一些挑战。
如何实现对电动汽车不同轮子上的驱动力精确控制是一个复杂的技术问题，需要借助先进的传感器技术和控制算法。
分布式电动汽车驱动力分配控制方法的研究需要跨学科的合作和交叉融合，这对研究团队和研究人员的综合素质提出了更高的要求。
随着电动汽车技术的不断发展和市场需求的不断增长，分布式电动汽车驱动力分配控制方法将会迎来新的发展机遇和挑战。
5. 个人观点和理解对于分布式电动汽车驱动力分配控制方法，我认为它是电动汽车技术发展过程中的一个重要环节，关系到电动汽车的性能和安全。
基于CarsimSimulink联合仿真的分布式驱动电动汽车建模一、本文概述随着电动汽车技术的快速发展，分布式驱动电动汽车（Distributed Drive Electric Vehicles, DDEV）因其高效能源利用、优越操控性能以及灵活的驱动方式，正逐渐成为新能源汽车领域的研究热点。
为了更深入地理解和研究DDEV的动态特性与控制策略，建立精确的车辆模型是关键。
本文旨在探讨基于Carsim与Simulink 联合仿真的分布式驱动电动汽车建模方法，以期在车辆动力学建模、控制策略优化和系统集成等方面提供有效的技术支撑。
本文首先介绍分布式驱动电动汽车的基本结构和特点，阐述其相较于传统车辆的优势。
随后，详细介绍Carsim和Simulink两款软件在车辆建模和仿真分析方面的功能和特点，以及它们联合仿真的优势。
接着，将重点介绍如何利用Carsim建立DDEV的车辆动力学模型，包括车辆动力学方程、轮胎模型、驱动系统模型等。
将探讨如何利用Simulink构建DDEV的控制策略模型，包括驱动控制、制动控制、稳定性控制等。
在建立了DDEV的车辆动力学模型和控制策略模型后，本文将详细阐述如何将这两个模型进行联合仿真，并分析仿真结果。
通过对比分析不同控制策略下的车辆性能表现，验证所建模型的准确性和有效性。
本文还将讨论分布式驱动电动汽车建模面临的挑战和未来的研究方向，为相关领域的研究者提供参考和借鉴。
二、Carsim软件介绍Carsim是一款由密歇根大学开发的高级车辆动力学仿真软件，广泛应用于车辆控制、车辆动力学、主动和被动安全、电动和混合动力车辆以及先进的驾驶员辅助系统等领域的研究和开发。
该软件以模块化的方式集成了车辆各个子系统的动力学模型，包括发动机、传动系统、制动系统、转向系统、悬挂系统、轮胎以及车身等。
Carsim的核心优势在于其强大的物理引擎和精确的仿真能力。
通过精确的算法和详尽的车辆参数数据库，Carsim能够模拟出车辆在各种道路条件和驾驶操作下的动态行为，如加速、制动、转向、侧滑等。
分布式驱动电动汽车AFS和DYC协调控制策略研究摘要随着人们对环境保护意识的不断提高，电动汽车被越来越广泛地应用。
然而，电动汽车的安全性能和驾驶体验仍然需要提高。
本文针对电动汽车的自适应前照灯系统（AFS）和动态稳定控制系统（DYC）进行研究，提出了一种分布式驱动电动汽车AFS和DYC协调控制策略。
首先，通过分析电动汽车的动力学模型和AFS控制原理，建立了分布式控制模型，使得AFS能够自适应调整前照灯照射范围并且反映动态路况。
其次，通过研究电动汽车的离散控制模型和DYC控制原理，提出了一种基于模型预测控制的DYC协调控制策略。
该策略采用了基于短期和长期预测的混合控制策略，有效地提高了电动汽车的稳定性和安全性。
最后，通过仿真实验对本文协调控制策略的有效性进行了验证。
实验结果显示，该策略能够使AFS和DYC系统之间实现协同控制，同时保持较高的车速和良好的驾驶舒适性。
这些结果为电动汽车的安全性能和驾驶体验的提升提供了一种新的思路。
关键词：电动汽车；自适应前照灯系统；动态稳定控制；协调控制AbstractWith the increasing awareness of environmental protection, electric vehicles have been widely used. However, the safety performance and driving experience of electric vehicles still need to be improved. This paper focuses on the research of the Adaptive Front-lighting System (AFS) and Dynamic Stability Control (DYC) of electric vehicles, and proposes a distributed driving electric vehicle AFS and DYC coordinated control strategy.Firstly, by analyzing the dynamics model and AFS control principle of electric vehicles, a distributed control model was established, so that AFS could adaptively adjust the illumination range of headlights and reflect the dynamic road conditions. Secondly, based on the study of the discrete control model and DYC control principle of electric vehicles, a model predictive control-based DYC coordinated control strategy was proposed. The strategy adopted a mixed control strategy based on short-term and long-term prediction, effectively improving the stability and safety of electric vehicles.Finally, the validity of the coordinated control strategy proposed in this paper was verified bysimulation experiments. The experimental results show that the strategy can achieve coordinated control between the AFS and DYC systems while maintaining high speed and good driving comfort. These results provide a new approach for improving the safety performance and driving experience of electric vehicles.Keywords: electric vehicle; adaptive front-lighting system; dynamic stability control; coordinated controElectric vehicles have gained significant popularityin recent years due to their environmentalfriendliness and low operating costs. However, the safety performance and driving experience of electric vehicles have always been a major concern for consumers. In particular, the adaptive front-lighting system (AFS) and dynamic stability control (DYC) are essential systems that affect the safety and comfort of driving. Therefore, coordinated control between the AFS and DYC systems is very critical for electric vehicles.Previous studies have mainly focused on the independent control of the AFS and DYC systems. However, the coupling effect between these two systems has been ignored in previous studies. This paper proposes a coordinated control strategy that considersthe coupling effect between the AFS and DYC systems, and investigates its effectiveness by simulation experiments.The coordinated control strategy proposed in this paper utilizes a hierarchical control framework. The upper level of the control framework is responsiblefor the coordination between the AFS and DYC systems, while the lower level is responsible for the independent control of each system. The coordination between the AFS and DYC systems is achieved by introducing a new control variable, which considers the coupling effect between these two systems.The simulation experiments conducted in this paper demonstrate that the proposed coordinated control strategy can effectively improve the safety performance and driving experience of electric vehicles. In particular, the results show that the strategy can achieve coordinated control between the AFS and DYC systems, while maintaining high speed and good driving comfort. This provides a new approach for improving the safety performance and driving experience of electric vehicles.In conclusion, this paper proposes a coordinated control strategy that considers the coupling effectbetween the AFS and DYC systems, and investigates its effectiveness by simulation experiments. The experimental results demonstrate that the proposed strategy can significantly improve the safety performance and driving experience of electric vehicles. Therefore, this paper provides a valuable contribution to the research on improving the safety performance and driving experience of electric vehiclesIn recent years, the usage of electric vehicles has been increasing due to the concerns for environment pollution and energy conservation. As a result, it is essential to ensure the safety performance and driving experience of electric vehicles to enhance their marketability and customer satisfaction. One significant concern for electric vehicles is their stability during cornering, which can be affected by factors such as velocity, steering angle, and road surface conditions. Hence, it is essential to have a mechanism that can improve the stability of electric vehicles during cornering.One potential mechanism for improving the stability of electric vehicles during cornering is the integration of the active front steering (AFS) and direct yaw moment control (DYC) systems. The AFS system can helpimprove the steering response of the electric vehicle, while the DYC system can improve the vehicle'sstability by generating a yaw moment in response to the steering angle and vehicle velocity.However, the coupling effect between the AFS and DYC systems can significantly affect the performance of the vehicle. Thus, this paper proposes a coordinated control strategy that considers the coupling effect between the AFS and DYC systems to enhance the safety performance and driving experience of electric vehicles.The proposed strategy was tested using simulation experiments, and the results demonstrated significant improvements in the safety performance and driving experience of electric vehicles. Specifically, the simulations showed that the proposed control strategy can improve the vehicle's stability during cornering, leading to a reduction in yaw rate and lateral acceleration. Furthermore, the strategy can improve the responsiveness of the steering system by reducing the delay in the steering response, which can lead to a better driving experience for the driver.In conclusion, this paper provides a valuable contribution to the research on improving the safetyperformance and driving experience of electric vehicles. The coordinated control strategy proposed in this paper considers the coupling effect between the AFS and DYC systems, leading to significant improvements in the safety performance and driving experience of electric vehicles. Future research can further investigate the proposed control strategy by conducting more experiments on different electric vehicles to verify its effectivenessIn addition to the proposed coordinated control strategy, there are several other areas of research that can contribute to the improvement of the safety performance and driving experience of electric vehicles.One such area is the development of advanced driver assistance systems (ADAS) specifically designed for electric vehicles. ADAS can include features such as collision avoidance, lane departure warnings, and automated parking, all of which can help increase the safety of electric vehicles on the road.Another area of research is the development of more efficient and reliable battery technology. Improvements in battery technology can lead to longer driving ranges and faster charging times, makingelectric vehicles more practical and convenient for everyday use.Finally, research can also focus on improving the overall infrastructure for electric vehicles. This can include increasing the number of charging stations available, improving the speed and convenience of charging, and developing smarter grid technologiesthat can optimize the use of renewable energy sources.Overall, continued research and development in these areas can help increase the safety, efficiency, and convenience of electric vehicles, paving the way for a more sustainable and environmentally friendly transportation systemIn conclusion, electric vehicles have the potential to significantly reduce greenhouse gas emissions from transportation, but there are still challenges that need to be addressed to fully realize their benefits. Improving battery technology, increasing the range of vehicles, and developing smart charging and grid technologies are all important areas for research and development. Additionally, infrastructure improvements such as increasing the number and convenience of charging stations can help support the growth of electric vehicles. By addressing these challenges andinvesting in the continued development of electric vehicle technology, we can create a more sustainable and environmentally friendly transportation system。
分布式电动汽车操纵稳定性仿真分析肖文文;张缓缓;轩飞虎【摘要】基于Carsim/Simulink对轮毂电机式电动汽车操纵稳定性的研究,建立轮毂电机式电动汽车的整车模型.通过分析在同一实验工况下轮毂电机驱动电动汽车和传统汽车对操纵稳定性的区别.通过对轮毂电机式电动汽车的非簧载质量、行驶速度、路面摩擦系数仿真分析,从而确定主要影响稳定性的因素.另外通过双移线仿真实验仿真实验分析该模型的优劣.主要通过轮毂电机式电动汽车的侧向加速度、横摆角速度和质心侧偏角等参数评价确定其操纵稳定性.【期刊名称】《制造业自动化》【年(卷),期】2019(041)003【总页数】5页(P86-89,154)【关键词】轮毂电机;电动汽车;仿真分析;Carsim/Simulink【作者】肖文文;张缓缓;轩飞虎【作者单位】上海工程技术大学,上海201620;上海工程技术大学,上海201620;上海工程技术大学,上海201620【正文语种】中文【中图分类】U4690 引言汽车的操纵稳定性主要包括稳定性和操纵性，两者互相影响。
另外稳定性主要是由横向稳定性和纵向稳定性组成的[1]。
汽车的操纵稳定主要是由地面和轮胎间的力决定，包括侧向力、纵向力以及垂直载荷[2]。
当轮胎与路面间的侧向力达到附着极限会引起轮胎的侧滑，当轮胎与路面间的纵向力达到附着系数时将引起轮胎打滑现象。
采用轮毂电机驱动式电动汽车，其主要有以下结构特点：1）簧下质量增加，簧下质量的增加将会间接的引起路面不平下车轮振动幅度加大，使得轮胎的接地性变差；2）转向系转动惯量增加，使得方向盘的输入响应变差，回正性能变差；3）整车质量的分布变化，使得影响前后悬架偏频和振动特性、转向特性变化和横摆响应变化；4）轮毂电机力矩波动及控制精度，使得方矩波动引起车辆振动和左右车轮力矩误差引起附加横摆运动。
另外轮毂电机式驱动电动汽车的结构使得主销偏距增加从而使得电动汽车的稳定性变差[3]。
轮毂电机式电动汽车与传统汽车相比少了减震器、差速器和传动轴等机械零件，直接通过控制轮毂电机控制电动汽车的行驶状态。
基于转矩协调分配的分布式驱动电动汽车稳定性控制张细政;郑亮【摘要】提出一种基于车轮转矩优化分配的层次化车辆稳定性控制方法,用于分布式驱动电动汽车的操纵稳定性控制.建立八自由度车辆模型,分三层设计控制系统,上层控制器以质心侧偏角和横摆角速度为状态变量,采用积分二自由度控制模型,引入虚拟控制解耦两控制变量,计算车辆稳定的等效横摆力矩;中层采用线性二次型方法,优化分配前后轮转向角和轮胎纵向力;下层控制器设计滑模滑移率控制器,完成定滑移率下的车轮转矩再分配.仿真结果表明,该控制系统在高速极限工况下能充分利用轮胎的附着潜力,实现车轮转矩的协调分配,提高车辆的操纵稳定性;当执行机构出现故障时,系统能有效重构并实现控制量再分配,提高车辆的安全性.【期刊名称】《中国机械工程》【年(卷),期】2018(029)015【总页数】8页(P1780-1787)【关键词】分布式驱动电动汽车;稳定性控制;控制分配;滑移率控制【作者】张细政;郑亮【作者单位】湖南工程学院电气信息学院,湘潭,411104;湖南工程学院电气信息学院,湘潭,411104【正文语种】中文【中图分类】U461.60 引言车辆稳定性控制要求汽车行驶在一理想轨迹的同时，车辆状态始终跟随理想状态。
近年来，将电机置于车轮内，车轮采用独立电机作为驱动源的新型分布式驱动电动汽车（distributed-driven electric vehicle，DEV）得到了广泛关注。
在分布式驱动形式下，各轮驱动/制动转矩独立可控，只需结合汽车运行状态直接对电机施加控制，便可以精确地将转矩控制分配到每个车轮［1-2］。
因此，获得可物理实现的纵向力与转矩，并将其协调地分配到4个车轮上，是实现DEV操纵稳定的关键性问题。
从已有研究文献来看，DEV稳定性控制多采用层次化的结构，控制上层为横摆力矩控制器设计，下层为横摆力矩的控制分配［3-9］。
横摆力矩控制器完成横摆力矩的决策和计算，根据车辆当前状态与参考值的误差计算出所需的期望横摆力矩。
分布式驱动电动汽车操纵稳定性控制评价体系余卓平;肖振宇;冷搏;王竑博;熊璐【摘要】Based on features of distributed drive electric vehicle dynamic control system, an objective evaluation system for dynamic control systems of distributed drive electric vehicles was established. The evaluation system consists of performance evaluation parameters, evaluation methods and marking criteria. Performance evaluation was conducted in aspects of the vehicle and the dynamics control. Vehicle handling stability tests were carried out to assess a vehicle stability controller with the proposed evaluation system and to verify rationality and feasi-bility of the evaluation system itself.%基于分布式驱动电动车动力学控制系统的特点,设计了一套客观评价体系,用于评价分布式驱动电动车动力学控制系统的性能.评价体系包括性能评价项目、评价方法和评分准则3个方面.性能评价项目涵盖整车层面和动力学控制系统层面.利用提出的评价体系对搭载动力学控制的车辆进行了操纵稳定性试验评价,验证了评价体系的合理性和可行性.【期刊名称】《华东交通大学学报》【年(卷),期】2016(033)005【总页数】8页(P25-32)【关键词】操纵稳定性;评价体系;车辆动力学控制;分布式驱动电动汽车【作者】余卓平;肖振宇;冷搏;王竑博;熊璐【作者单位】同济大学中德学院,上海 200092;同济大学汽车学院,上海 201804;同济大学中德学院,上海 200092;同济大学汽车学院,上海 201804;同济大学汽车学院,上海 201804;同济大学汽车学院,上海 201804【正文语种】中文【中图分类】U461;U467.1分布式驱动电动车具有各轮独立驱动且驱动力矩可控等特点，其动力学控制方法一直是各大企业及高校研究的焦点［1］。
10.16638/ki.1671-7988.2019.24.001分布式驱动电动汽车整车动力学模型仿真与分析陈磊，李强，胡乾斌，赵璐，吴坚（浙江科技学院机械与能源工程学院，浙江杭州310023）摘要：为研究分布式驱动电动汽车驱动对整车操纵稳定性的影响，建立较为准确的汽车动力学模型是重要的前提。
在MA TLAB/Simulink环境下建立分布式驱动电动汽车七自由度动力学模型，进行两驱和四驱的整车动力学仿真和分析，用CarSim软件验证所建模型精确度。
仿真结果表明：建立的汽车动力学模型在角阶跃工况和正弦函数工况下，横摆角速度和质心侧偏角误差范围均在7%以内，可以真实地反映车辆运动特性的变化，为后续整车智能控制算法制定和验证性能等打下良好的仿真基础。
关键词：分布式驱动；电动轮汽车；整车动力学模型；仿真中图分类号：U469.72 文献标识码：A 文章编号：1671-7988(2019)24-01-03Simulation and Analysis of Dynamic Model of Distributed Drive Electric VehicleChen Lei, Li Qiang, Hu Qianbin, Zhao Lu, Wu Jian( School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology,Zhejiang Hangzhou 310023 )Abstract: In order to study the influence of distributed drive electric wheel on vehicle handling stability, it is an important prerequisite to establish a more accurate vehicle dynamics model. a seven-degree-of-freedom dynamic model of distributed drive electric vehicle is established under the environment of MA TLAB/Simulink. The dynamic simulation and analysis of two-wheel and four-wheel vehicles are carried out. The accuracy of the model is verified by CarSim software. The simulation results show that the yaw angular velocity and sideslip error range of the center of mass are within 7% under the angular step and sinusoidal function conditions, which can truly reflect the change of vehicle motion characteristics and lay a good simulation foundation for the formulation and validation of subsequent vehicle intelligent control algorithm. Keywords: Distributed drive; Electric vehicle; Vehicle dynamics model; SimulationCLC NO.: U469.72 Document Code: A Article ID: 1671-7988(2019)24-01-03前言相比于传统的燃油汽车尾气污染，新能源汽车的零污染的优势越来越受到人们的重视。
