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Robust Cooperative Control of Multiple Autonomous Vehicles for Platoon Formation Considering Parameter Uncertainties

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Automotive Innovation 2020年第1期3卷 88-100页

作者： weichao zhuang Liwei Xu Guodong Yin School of Mechanical Engineering Southeast UniversityNanjing 211189China

This paper proposes a robust cooperative control strategy for multiple autonomous vehicles to achieve safe and efficient platoon formation,and it analyzes the effects of vehicle stability boundaries and parameter *** cooperative vehicle control framework is composed of the upper planning level and lower tracking control *** the planning level,the trajectory of each vehicle is generated by using the multi-objective flocking algorithm to form the *** parameters of the flocking algorithm are optimized to prevent the vehicle speed and yaw rate from going beyond their *** the lower level,to realize the stable platoon formation,a lumped disturbance observer is designed to gain the stable-state reference,and a distributed robust model predictive controller is proposed to achieve the offset-free trajectory tracking while downsizing the effects of parameter *** simulation results show the proposed cooperative control strategy can achieve safe and efficient platoon formation.

关键词： Platoon formation Robust model predictive controller Multiple autonomous vehicles Parameter uncertainty

Integrated energy-oriented cruising control of electric vehicle on highway with varying slopes considering battery aging

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Science China(Technological Sciences) 2020年第1期63卷 155-165页

作者： zhuang weichao QU LingHu XU ShaoBing LI BingBing CHEN Nan YIN GuoDong School of Mechanical Engineering Southeast UniversityNanjing 211189China Department of Mechanical Engineering University of MichiganAnn Arbor 48105USA

Eco-driving strategies for vehicles with conventional powertrains have been studied for years and attempt to reduce fuel consumption by optimizing the driving velocity *** electric vehicles(EVs)with regenerative braking,the speed profile with the best energy efficiency should be different from conventional *** paper proposes an energy-oriented cruising control strategy for EVs with a hierarchical structure to realize eco-cruising on highways with varying *** upper layer plans the energy-optimized vehicle velocity,and the lower layer calculates the torque allocation between the front and rear ***,the resulting speed profile with varying velocity may cause a high charge and discharge rate of the battery,resulting in rapid battery *** extend the battery life,we make a tradeoff between the energy consumption and wear of the battery by formulating an optimal control problem,where driving comfort and travel time are also *** indirect optimal control method is implemented to derive the optimal control *** an extension,the control rule for avoiding rear-end collisions is presented and simulated for driving in the real world.

关键词： eco-driving electric vehicle battery fading model dynamic programming energy management

Adaptive Multi-modal Fusion Instance Segmentation for CAEVs in Complex Conditions:Dataset,Framework and Verifications

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Chinese Journal of Mechanical Engineering 2021年第5期34卷 96-106页

作者： Pai Peng Keke Geng Guodong Yin Yanbo Lu weichao zhuang Shuaipeng Liu School of Mechanical Engineering Southeast UniversityNanjingChina

Current works of environmental perception for connected autonomous electrified vehicles(CAEVs)mainly focus on the object detection task in good weather and illumination conditions,they often perform poorly in adverse scenarios and have a vague scene parsing *** paper aims to develop an end-to-end sharpening mixture of experts(SMoE)fusion framework to improve the robustness and accuracy of the perception systems for CAEVs in complex illumination and weather *** original contributions make our work distinctive from the existing relevant *** Complex KITTI dataset is introduced which consists of 7481 pairs of modified KITTI RGB images and the generated LiDAR dense depth maps,and this dataset is fine annotated in instance-level with the proposed semi-automatic annotation *** SMoE fusion approach is devised to adaptively learn the robust kernels from complementary *** comparative experiments are implemented,and the results show that the proposed SMoE framework yield significant improvements over the other fusion techniques in adverse environmental *** research proposes a SMoE fusion framework to improve the scene parsing ability of the perception systems for CAEVs in adverse conditions.

关键词： Connected autonomous electrified vehicles Multi-modal fusion Semi-automatic annotation Sharpening mixture of experts Comparative experiments

Integrated energy-oriented lateral stability control of a four-wheelindependent-drive electric vehicle

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Science China(Technological Sciences) 2019年第12期62卷 2170-2183页

作者： LIU JingXing zhuang weichao ZHONG Hong WANG LiangMo CHEN HeJuan TAN Chin-An School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China School of Mechanical Engineering Southeast UniversityNanjing 211189China Department of Mechanical Engineering University of MichiganAnn Arbor MI 48109USA School of Mechanical Engineering Wanjiang University of TechnologyMa'anshan 243031China Department of Mechanical Engineering Wayne State UniversityDetroit MI 48202USA

Improving the energy efficiency of an electric vehicle(EV) is an effective approach to extend its driving range. This paper proposes an integrated energy-oriented lateral stability controller(IESC) for a four-wheel independent-drive EV(4 WID-EV) to optimize its energy consumption while maintaining vehicular stability during cornering. The IESC is a hierarchical controller with two levels. The high-level decision-making controller determines the virtual control inputs, i.e., the desired additional yaw moment and total wheel torque, while the low-level controller allocates the motor torques according to the virtual control *** the high-level controller, the desired additional yaw moment is first calculated using a linear quadratic regulator(LQR) to minimize the control expenditure. Meanwhile, a stability weighting factor(SWF) based on phase plane analysis is proposed to adjust the additional yaw moment, which can reduce the additional energy consumption caused by the mismatch between the reference model and the actual vehicle. In addition to the yaw moment, the desired total wheel torque is calculated using a proportional-integral(PI) controller to track the desired longitudinal velocity. In the low-level controller, a multi-objective convex-optimization problem is established to optimize the motor torque by minimizing the energy consumption and considering the tire-road frictional limit and motor saturation. A globally optimal solution is obtained by using an active-set method. Finally,double-lane change(DLC) simulations are conducted using Car Sim and MATLAB/Simulink. The simulation results demonstrate that the proposed controller achieves great lateral stability control performance and reduces the energy consumption by5.23% and 2.95% compared with the rule-based control strategy for high-and low-friction DLC maneuvers, respectively.

关键词： four-wheel-independent-drive electric vehicle energy-oriented lateral stability torque allocation

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

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Chinese Journal of Mechanical Engineering 2021年第5期34卷 44-55页

作者： Haoxuan Dong weichao zhuang Guodong Yin Liwei Xu Yan Wang Fa’an Wang Yanbo Lu School of Mechanical Engineering Southeast UniversityNanjing 211189China

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity *** the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic ***,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking ***,a double-layer control scheme is *** the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking *** the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and *** simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking ***,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

关键词： Connected electric vehicles Energy optimization Velocity planning Regenerative braking Dynamic programming Model predictive control

An Integrated Control Framework for Torque Vectoring and Active Suspension System

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Chinese Journal of Mechanical Engineering 2024年第1期37卷 62-73页

作者： Jiwei Feng Jinhao Liang Yanbo Lu weichao zhuang Dawei Pi Guodong Yin Liwei Xu Pai Peng Chaobin Zhou School of Mechanical Engineering Southeast UniversityNanjing 211189China School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China School of Mechano-Electronic Engineering Lanzhou University of TechnologyLanzhou 730050China

Four-wheel independently driven electric vehicles(FWID-EV)endow a flexible and scalable control framework to improve vehicle *** paper integrates the torque vectoring and active suspension system(ASS)to enhance the vehicle’s longitudinal and vertical motion control *** the nonlinear characteristic of the tire model leads to a relatively heavier computational *** facilitate the controller design and ease the load,a half-vehicle dynamics system is built and simplified to the linear-time-varying(LTV)*** a model predictive controller is developed by formulating the objective function by comprehensively considering the safety,energy-saving and comfort *** in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy ***,the effectiveness of the proposed controller is verified through the rapid-control-prototype(RCP)*** results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

关键词： Four-wheel independently driven electric vehicles Tire nonlinearity Linear-time-varying(LTV)model Model predictive control Rapid control prototype

Recognition Method for Multi-Class Motor Imagery EEG Based on Channel Frequency Selection

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Recognition Method for Multi-Class Motor Imagery EEG Based o...

Strategy for Heterogeneous Vehicular Platoons Merging in Automated Highway System

第37届中国控制会议

作者： Deming Zhang Guodong Yin weichao zhuang Xianjian Jin School of Mechanical Engineering Southeast University State Key Laboratory of Automotive Simulation and Control Jilin University

The problem of the classification for binary motor imagery EEG has been widely studied and great achievement has been made. However, it is difficult to get good recognition rate for multi-class motor imagery EEG due to its low signal-to-noise ratio（SNR）. In order to improve the classification accuracy of multi-class motor imagery EEG, an EEG recognition method based on channel frequency selection is proposed. First, the original EEG signals are filtered by different frequency bands, and the corresponding band power can be calculated. Then the separability information of each frequency band is obtained by using the Fisher distance. Several bands with the maximum Fisher distance in each channel are selected for filtering. Finally, the feature vector of the filtered EEG signal is extracted by one-versus-one CSP（OVO-CSP） and classified by support vector machine（SVM）. The public dataset of four-class motor imagery EEG is applied to evaluate this method. The results indicate that the classification accuracy and the Kappa coefficient achieved by the proposed method can reach 86.85% and 0.825 respectively, remarkably higher than the traditional method using a broad band. Therefore, the frequency bands associated with motor imagery can be effectively selected by this method, which can improve the recognition performance for multi-class motor imagery EEG significantly.

关键词： multi-class motor imagery EEG recognition channel frequency selection OVO-CSP SVM

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Strategy for Heterogeneous Vehicular Platoons Merging in Aut...

第30届中国控制与决策会议

作者： Hao Liu weichao zhuang Guodong Yin Zhuoren Tang Liwei Xu School of Mechanical Engineering Southeast University

In automated highway systems(AHSs) vehicles are expected to travel in a way that safety and high capacity are guaranteed by interacting with automated vehicles in the vicinity. The goal of this paper is to study the problem of heterogeneous vehicular platoons merging which is one of the crucial vehicle maneuvers in an AHS environment that could affect safety and capacity. For this purpose, a specific protocol based on Linear Quadratic Regulator(LQR) Controller is designed to make space for the merging platoon, and a Distributed Model Predictive Control(DMPC) controller is proposed to generate trajectories when several automated vehicles merge from the adjacent lane into the main vehicle platoon. Performances of designed controllers are tested in platoon merging scenario when multiple vehicles change lane to join the destination platoon, and the simulation results demonstrate the feasibility of the proposed approaches while taking the safety and comfort of passengers into account.

关键词： Automated highway systems(AHS) vehicular platoons merging and Distributed Model Predictive Control (DMPC)

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网联电动汽车信号灯控路口经济性驾驶策略

东南大学学报（自然科学版） 2021年第1期51卷 178-186页

作者：陈浩庄伟超殷国栋董昊轩东南大学机械工程学院南京210096

针对智能网联电动汽车在信号灯控路口的经济性驾驶问题,提出一种基于最优控制的经济性驾驶车速优化策略.首先,构建包含信号灯、车速限制等约束,以能量消耗最小化为目标的信号灯控路口车辆速度优化问题;然后,利用庞特里亚金极小值原理解... 详细信息

针对智能网联电动汽车在信号灯控路口的经济性驾驶问题,提出一种基于最优控制的经济性驾驶车速优化策略.首先,构建包含信号灯、车速限制等约束,以能量消耗最小化为目标的信号灯控路口车辆速度优化问题;然后,利用庞特里亚金极小值原理解析求解最优控制率;考虑到动态交通场景中车辆对未来交通信息的预测能力有限、信号灯约束条件多变等特点,提出了一种双层滚动距离域车速优化策略,将信号灯控路口经济性驾驶问题转化为分段最优控制问题,得到分段最优速度轨迹.仿真结果表明:在有限预测能力和无限预测能力2种情况下,所提出的经济性驾驶车速优化策略较加速—匀速—制动策略分别有9.2%和10.3%的能量节省;随着预测距离和信号灯控路口通行速度的增大,在提高通行效率的同时,能量节省效率进一步提高.

关键词：经济性驾驶智能网联汽车信号灯控路口滚动优化庞特里亚金极小值原理