Driving Condition Recognition Based on HMM for HEV Control
عنوان مقاله: Driving Condition Recognition Based on HMM for HEV Control
شناسه ملی مقاله: ISME16_915
منتشر شده در شانزدهمین کنفرانس سالانه بین المللی مهندسی مکانیک در سال 1387
شناسه ملی مقاله: ISME16_915
منتشر شده در شانزدهمین کنفرانس سالانه بین المللی مهندسی مکانیک در سال 1387
مشخصات نویسندگان مقاله:
Morteza Montazeri-Gh - Systems Simulation and Control Laboratory, Mechanical Engineering Department, Iran University of Science and Technology, Narmak, Tehran, Iran
Amir Ahmadi - Systems Simulation and Control Laboratory, Mechanical Engineering Department, Iran University of Science and Technology, Narmak, Tehran, Iran
خلاصه مقاله:
Morteza Montazeri-Gh - Systems Simulation and Control Laboratory, Mechanical Engineering Department, Iran University of Science and Technology, Narmak, Tehran, Iran
Amir Ahmadi - Systems Simulation and Control Laboratory, Mechanical Engineering Department, Iran University of Science and Technology, Narmak, Tehran, Iran
This paper presents a methodological approach for driving pattern recognition and prediction for Hybrid Electric Vehicle (HEV) control. In this approach, based on data collection in the real traffic conditions, several driving patterns are classified. These driving patterns represent different traffic conditions. Markov chain modeling has been used for traffic condition prediction. The driving pattern prediction can then be utilized for the HEV adaptive control. The simulation results are presented to investigate the effectiveness of the approach for the driving pattern prediction.
کلمات کلیدی: microtrip, traffic condition, driving pattern, Markov chain, recognition, prediction
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/41491/