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State Estimation of vehicle’s dynamic Stability Based on the Nonlinear Kalman Filter

Automotive Innovation 2018年第3期1卷 281-289页

作者： Xiaofei Pei Xu Hu Wei Liu Zhenfu Chen Bo Yang School of Automotive Engineering Wuhan University of TechnologyWuhan 430070China Wanxiang Qianchao Corporation Hangzhou 311215China

An accurate estimation of a vehicle’s state of motion is the basis of dynamic stability *** different nonlinear Kalman filters are adopted for the estimation of the vehicle’s lateral/rollover stability ***,the overall structure of the state estimation with four inputs and four outputs is *** determining tire-cornering stiffness using a recursive leastsquares(RLS)method,the equations of state and of observation for the nonlinear Kalman filter are established based on a vehicle model with four degrees of freedom including planar and rollover ***,the specific steps of real-time state estimation using the extended Kalman filter(EKF)and unscented Kalman filter(UKF)are both *** a co-simulation,we find that the RLS algorithm estimates tire-cornering stiffness accurately and quickly,and the UKF improves the effect of state estimation compared with *** addition,the UKF is verified against data from vehicle *** results show the proposed method is reliable and practical in estimating vehicle states.

关键词： vehicle dynamic State estimation EKF UKF vehicle test

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PSD identification for the mining trucks with HPS based on the IFFT and wavelet analysis

PSD identification for the mining trucks with HPS based on t...

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2023智能制造与机械动力学学术大会

作者： Jianwei Wu Qidi Fu Xuemei Li Beibei Sun

Because the vehicle dynamic model with the hydro-pneumatic suspension(HPS) is a strongly nonlinear system,the traditional random vibration theory cannot be used for obtaining the pavement *** this paper,therefore,the responses in the time domain are obtained by using the inverse fast Fourier transformation(IFFT) which can generate the time domain model of the unevenness road for the nonlinear vehicle ***,the wavelet analysis is used for processing the experimental data according to the excitation ***,the corrected unevenness index(expressing the PSD) in the test site can be obtained by matching the simulation and experimental *** research provides an approach for correcting the road PSD in test site according to the responses from the vibration test,particularly with the strong nonlinear suspension.

关键词： HPS road spectrum wavelet analysis IFFT vehicle dynamic

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A Cloud Based and Real Time Kinematic Sensing Solution for Automated Parking Function

A Cloud Based and Real Time Kinematic Sensing Solution for A...

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作者： David BARBé Xin YANG Zeng-hong CHEN Hao YE Ting CHEN Si-yuan FAN Xiao-yuan CAI Ya-ting GUO Tao YANG Department of Electrification Transmission and Vehicle AVL Technical Center （Shanghai） Co.Ltd

Automated Valet Parking is foreseen as a highly automated function to be implemented on large scale in mass production in the near future. For such function, the authors have developed an innovative system concept using both real time kinematic sensing system and infrastructure IoT（Internet of things） camera to perform AVP function. As the driver activates the AVP function, the infrastructure identifies available parking spots by processing in real time camera frames and as the path is computed, the vehicle executes automated parking maneuvers. This paper introduces the system scheme and system engineering approach as well as key technology bricks to realize AVP function and proves the effectiveness and accuracy of the system through extensive vehicle testing. From system definition to final prototype validation, through Motion control algorithm description or deep learning algorithm tuning method, this paper covers a large spectrum of the engineering domains required to implement such function. The development approach is focused on a user perspective by emphasizing simplicity of usage, frugality of the solution and robustness of the system.

关键词： Autonomous Driving vehicle dynamic Deep learning Motion Control Real Time Kinematic Infrastructure Connectivity Internet of Things

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Pursuit Model Development and Calibration Methodology for Automated Parking Function

Pursuit Model Development and Calibration Methodology for Au...

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第32届中国控制与决策会议

作者： David Barbe Xin Yang Zenghong Chen Hao Ye Ting Chen Siyuan Fan Xiaoyuan Cai Yating Guo Tao Yang Department of Electrification Transmission and Vehicle AVL Technical Center （Shanghai） Co. Ltd

Automated Valet Parking is foreseen as a highly automated function to be implemented on large scale in mass production in the near future. For such function, The authors have developed an innovative system concept using both real time kinematic sensing system and infrastructure IoT（Internet of things） camera to perform AVP function. As the driver activates the AVP function, the infrastructure identifies available parking spots by processing in real time camera frames and as the path is computed, the vehicle executes automated parking maneuvers. This paper introduces the system scheme and system engineering approach as well as key technology bricks to realize AVP function and proves the effectiveness and accuracy of the system through extensive vehicle testing. From system definition to final prototype validation, through Motion control algorithm description or deep learning algorithm tuning method, this paper covers a large spectrum of the engineering domains required to implement such function. Finally a specific Pursuit Model development and calibration approach is elicited for the motion control function and proven in use by AVL vehicle Prototype platform.

关键词： Autonomous Driving vehicle dynamic Deep learning Motion Control Real Time Kinematic Infrastructure Connectivity internet of Things

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