An Intelligent Identification Method of Vehicle Driving Cycle Based on LVQ Model

Wang, Yuefei; Zhang, Nan; Xia, Jingbao; Liu, Baijun; Wu, Yuan

doi:10.1109/iscid.2017.46

2017 10th International Symposium on Computational Intelligence and Design (ISCID) 2017

DOI: 10.1109/iscid.2017.46

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An Intelligent Identification Method of Vehicle Driving Cycle Based on LVQ Model

Yuefei Wang

Nan Zhang

Jingbao Xia

et al.

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2022

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Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles

Demir

Kocabiçak

2022

International Journal of Automotive Science and Technology

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This study presents a series of analyzes considering the traction and steering demands of an autonomous electric vehicle (AEV) as a shuttle. The considered analyzes in here are dealt with as driving cycle (DC) and driving scenarios (DS) to assess the traction and steering performance of the AEV. The aim of this study is to evaluate the issues such as over engineering for AEV traction and steering motor requirements on a certain route by comparatively analyzing traditional and dynamic calculation under the DC and DS. Therefore, DC and DS in the lit-erature are evaluated in terms of different applications, optimization techniques, generation algorithm, parametric characterization, e-motor type etc. Afterwards, NEDC, US06, WLTC, Double Lane Change (DLC), Constant Radius (CR) and Slowly Increase Steer (SIS) are determined. Then, they are arranged according to the vehicle-specific limits on an electric golf car. The modified DCs and DSs are run on the dynamic model of the vehicle. In the performed analysis, the parame-ters such as reference trajectory tracking, yaw angle, tractive and steering forces, lateral and longitudinal displacement-acceleration, steering and traction motor power–speed-torque are investigated. And the obtained results are evaluated by comparing the traditional calculation results.

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Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles

Demir

Kocabiçak

2022

International Journal of Automotive Science and Technology

View full text Add to dashboard Cite

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An Intelligent Identification Method of Vehicle Driving Cycle Based on LVQ Model

Cited by 1 publication

References 4 publications

Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles

Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles

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