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

Year 2022, Volume: 6 Issue: 4, 364 - 378, 31.12.2022

Uğur Demir , Zeliha Kamış Kocabıçak

https://doi.org/10.30939/ijastech..1178321
Cited By: 1

Abstract

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.

Keywords

Driving cycle Driving Scenario Autonomous Vehicle Steering and Traction Dynamics

Supporting Institution

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Project Number

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Thanks

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References

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Year 2022, Volume: 6 Issue: 4, 364 - 378, 31.12.2022

Uğur Demir , Zeliha Kamış Kocabıçak

https://doi.org/10.30939/ijastech..1178321
Cited By: 1

Abstract

Project Number

-

References

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  • [2] Demir U., Aküner M. C. Design and Analysis of Radiaxial In-duction Motor. Electrical Engineering. 2018; 100(4): 2361-2371.
  • [3] Christensen, T., Sørensen, N.B., Bøg, B. Energy Efficient Con-trol of an Induction Machine for an Electric Vehicle. Master Thesis, Aalborg University, Study Board of Industry and Glob-al Business Development, Denmark. 2012.
  • [4] Demir U., Aküner M. C. Design and Optimization of in-Wheel Asynchronous Motor for Electric Vehicle. Journal of the Facul-ty of Engineering and Architecture of Gazi University. 2018; 18(2): 1-21.
  • [5] Emirler M. T., Uygan İ. M. C., Güvenç B. A., Güvenç L.Robust PID Steering Control in Parameter Space for Highly Automated Driving. International Journal of Vehicular Technology. 2014; 259465: 1687-5702.
  • [6] Ji J., Khajepour A., Melek W. W., Huang Y. Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints. IEEE Transactions on Vehicular Technology. 2017; 66(2): 952-964.
  • [7] Emirler M. T., Wang H., Güvenç B.A. Automated robust path following control based on calculation of lateral deviation and Yaw angle error. ASME 2015 dynamic systems and control conference, Columbus, OH, p.V003T50A009. New York: ASME. 2015.
  • [8] Demir U., Aküner M. C. Using Taguchi method in defining critical rotor pole data of LSPMSM considering the power fac-tor and efficiency. Tehnički vjesnik. 2017; 24(2): 347- 353.
  • [9] Sun X., Shi Z., Lei G., Guo Y., Zhu J. Multi-Objective Design Optimization of an IPMSM Based on Multilevel Strategy. IEEE Transactions on Industrial Electronics. 2020; 68(1): 139-148.
  • [10] Guvenc B. A., Guvenc L. Robust two degree-of-freedom add-on controller design for automatic steering. IEEE Transactions on Control Systems Technology. 2002; 10(1): 137-148.
  • [11] Kocakulak T., Solmaz, H. Ön ve son iletimli paralel hibrit araçların bulanık mantık yöntemi ile kontrolü ve diğer güç sistemleri ile karşılaştırılması. Gazi Üniversitesi Mühendis-lik Mimarlık Fakültesi Dergisi. 2020; 35(4): 2269-2286.
  • [12] Snider J. M. Automatic Steering Methods for Autono-mous Automobile Path Tracking. Master Thesis, Robotics Insti-tute, Carnegie Mellon University, Pittsburgh, Pennsylvania. 2009. [13] Li L., Chaosheng H., Minghui L., Shuming S. Study on the combined design method of transient driving cycles for passenger car in Changchun. 2008 IEEE Vehicle Power and Propulsion Conference. 2008; 1-5.
  • [14] Zhuang J. H., Xie H.,Yan Y. Remote self-learning of driving cycle for electric vehicle demonstrating area. 2008 IEEE Vehicle Power and Propulsion Conference. 2008; 1-4.
  • [15] Liang Z. Xin Z., Yi T., Xinn Z. Intelligent Energy Man-agement Based on the Driving Cycle Sensitivity Identification Using SVM. 2009 Second International Symposium on Compu-tational Intelligence and Design. 2009; 513-516.
  • [16] Yi T., Xin Z., Liang Z., Xinn, Z. Intelligent Energy Management Based on Driving Cycle Identification Using Fuzzy Neural Network. 2009 Second International Symposium on Computational Intelligence and Design. 2009; 501-504.
  • [17] Shiqi O., Yafu Z., Jing L., Pu J., Baoyu T. Development of hybrid city bus's driving cycle. 2011 International Confer-ence on Electric Information and Control Engineering. 2011; 2112-2116.
  • [18] Zhuang J., Xie H., Li S., Yan Y., Zhu Z. Remote self-learning of driving cycle for hybrid electric vehicle. 2011 In-ternational Conference on Electrical and Control Engineering. 2011; 4029-4032.
  • [19] Liu L., Huang C., Lu B., Shi S., Zhang Y., Cheng J. Study on the design method of time-variant driving cycles for EV based on Markov Process. 2012 IEEE Vehicle Power and Propulsion Conference. 2012; 1277-1281.
  • [20] Chrenko D., Garcia Diez I., Le Moyne L. Artificial driving cycles for the evaluation of energetic needs of electric vehicles. 2012 IEEE Transportation Electrification Conference and Expo (ITEC). 2012; 1-5.
  • [21] Ma X., Ming W. Energy-saving driving mode for PHEV drivers based on energy cycle model. IET Hybrid and Electric Vehicles Conference 2013 (HEVC 2013). 2013; 1-5.
  • [22] Schwarzer V., Ghorbani R. Drive Cycle Generation for Design Optimization of Electric Vehicles. IEEE Transactions on Vehicular Technology. 2013; 62(1): 89-97.
  • [23] Shi S., et al. Research on Markov Property Analysis of Driving Cycle. 2013 IEEE Vehicle Power and Propulsion Con-ference (VPPC). 2013; 1-5.
  • [24] Asus, Z., Aglzim, E., Chrenko D., Daud Z. C., Le Moyne L. Dynamic Modeling and Driving Cycle Prediction for a Racing Series Hybrid Car. IEEE Journal of Emerging and Se-lected Topics in Power Electronics. 2014; 2(3): 541-551.
  • [25] Xing J., Han X., Ye H., Cui Y., Ye, H. Driving cycle recognition for hybrid electric vehicle. 2014 IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific). 2014; 1-6.
  • [26] Zhang B., Gao X., Xiong X., Wang X., Yang H. Devel-opment of the Driving Cycle for Dalian City. 2014 8th Interna-tional Conference on Future Generation Communication and Networking. 2014; 60-63.
  • [27] Nejad A. Z., Deilami S., Masoum M. A. S., Haghdadi N. Map-based linear estimation of drive cycle for hybrid electric vehicles. 2015 Australasian Universities Power Engineering Conference (AUPEC). 2015; 1-5.
  • [28] Nyberg P., Frisk E., Nielsen, L. Using Real-World Driv-ing Databases to Generate Driving Cycles With Equivalence Properties. IEEE Transactions on Vehicular Technology. 2016; 65(6): 4095-4105.
  • [29] Divakarla K. P., Emadi A., Razavi, S. N. Journey Map-ping—A New Approach for Defining Automotive Drive Cycles. IEEE Transactions on Industry Applications. 2016; 52(6): 5121-5129.
  • [30] Sun B. Driving cycle construction methodology based on Markov process and uniform distribution. 2016 35th Chi-nese Control Conference (CCC). 2016; 9300-9304.
  • [31] Chen Z., Li L. Yan B., Yang C., Marina Martínez C., Cao D. Multimode Energy Management for Plug-In Hybrid Electric Buses Based on Driving Cycles Prediction. IEEE Transactions on Intelligent Transportation Systems. 2016; 17(10): 2811-2821.
  • [32] Silvas E., Hereijgers K., Peng H., Hofman T., Steinbuch M. Synthesis of Realistic Driving Cycles With High Accuracy and Computational Speed, Including Slope Information. IEEE Transactions on Vehicular Technology. 2016; 65(6): 4118-4128.
  • [33] Liessner R., Dietermann A. M., Bäker B., Lüpkes K.Derivation of real-world driving cycles corresponding to traf-fic situation and driving style on the basis of Markov models and cluster analyses. 6th Hybrid and Electric Vehicles Confer-ence (HEVC 2016). 2016; 1-7.
  • [34] Wang Y., Zhang N., Xia J., Liu B., Wu Y. An Intelligent Identification Method of Vehicle Driving Cycle Based on LVQ Model. 2017 10th International Symposium on Computational Intelligence and Design (ISCID). 2017; 240-243.
  • [35] Mahayadin A. R., et al. Development of Driving Cycle Construction Methodology in Malaysia's Urban Road System. 2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA). 2018; 1-5.
  • [36] Zhang M., Shi S., Lin N., Yue B. High-Efficiency Driv-ing Cycle Generation Using a Markov Chain Evolution Algo-rithm. IEEE Transactions on Vehicular Technology. 2019; 68(2): 1288-1301.
  • [37] Sun R., Tian Y., Zhang H., Yue R., Lv B., Chen J. Da-ta-Driven Synthetic Optimization Method for Driving Cycle Development. IEEE Access. 2019; 7: 162559-162570.
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There are 84 citations in total.

Details

Primary Language English
Subjects Electrical Engineering
Journal Section Articles
Authors

Uğur Demir 0000-0001-7557-3637

Zeliha Kamış Kocabıçak 0000-0003-3292-8324

Project Number -
Publication Date December 31, 2022
Submission Date September 21, 2022
Acceptance Date November 10, 2022
Published in Issue Year 2022 Volume: 6 Issue: 4

Cite

APA Demir, U., & Kamış Kocabıçak, Z. (2022). Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles. International Journal of Automotive Science And Technology, 6(4), 364-378. https://doi.org/10.30939/ijastech..1178321
AMA Demir U, Kamış Kocabıçak Z. Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles. IJASTECH. December 2022;6(4):364-378. doi:10.30939/ijastech.1178321
Chicago Demir, Uğur, and Zeliha Kamış Kocabıçak. “Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles”. International Journal of Automotive Science And Technology 6, no. 4 (December 2022): 364-78. https://doi.org/10.30939/ijastech. 1178321.
EndNote Demir U, Kamış Kocabıçak Z (December 1, 2022) Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles. International Journal of Automotive Science And Technology 6 4 364–378.
IEEE U. Demir and Z. Kamış Kocabıçak, “Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles”, IJASTECH, vol. 6, no. 4, pp. 364–378, 2022, doi: 10.30939/ijastech..1178321.
ISNAD Demir, Uğur - Kamış Kocabıçak, Zeliha. “Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles”. International Journal of Automotive Science And Technology 6/4 (December 2022), 364-378. https://doi.org/10.30939/ijastech. 1178321.
JAMA Demir U, Kamış Kocabıçak Z. Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles. IJASTECH. 2022;6:364–378.
MLA Demir, Uğur and Zeliha Kamış Kocabıçak. “Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles”. International Journal of Automotive Science And Technology, vol. 6, no. 4, 2022, pp. 364-78, doi:10.30939/ijastech. 1178321.
Vancouver Demir U, Kamış Kocabıçak Z. Investigation on Different Driving Cycle and Scenarios Considering the Autonomous Electric Vehicles. IJASTECH. 2022;6(4):364-78.

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International Journal of Automotive Science and Technology (IJASTECH) is published by Society of Automotive Engineers Turkey

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