Torque Vectoring Control Strategies Comparison for Hybrid Vehicles with Two Rear Electric Motors
-
Published:2023-07-12
Issue:14
Volume:13
Page:8109
-
ISSN:2076-3417
-
Container-title:Applied Sciences
-
language:en
-
Short-container-title:Applied Sciences
Author:
de Carvalho Pinheiro Henrique1ORCID, Carello Massimiliana1ORCID, Punta Elisabetta2ORCID
Affiliation:
1. Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Torino, Italy 2. National Research Council of Italy, Institute of Electronics, Computer and Telecommunication Engineering, CNR-IEIIT, 10129 Torino, Italy
Abstract
In today’s automotive industry, electrification is a major trend. In-wheel electric motors are among the most promising technologies yet to be fully developed. Indeed, the presence of multiple in-wheel motors acting as independent actuators allows for the implementation of innovative active systems and control strategies. This paper analyzes different design possibilities for a torque vectoring system applied to an originally compact front-wheel drive hybrid electric vehicle with one internal combustion engine for the front axle and two added electric motors integrated in the wheels of the rear axle. A 14 degrees of freedom vehicle model is present o accurately reproduce the nonlinearities of vehicle dynamic phenomena and exploited to obtain high-fidelity numerical simulation results. Different control methods are compared, a PID, an LQR, and four different sliding mode control strategies. All controllers achieve sufficiently good results in terms of lateral dynamics compared with the basic hybrid version. The various aspects and features of the different strategies are analyzed and discussed. Chattering reduction strategies are developed to improve the performance of sliding mode controllers. For a complete overview, control systems are compared using a performance factor that weighs control accuracy and effort in different driving maneuvers, i.e., ramp and step steering maneuvers performed under quite different conditions ranging up to the limits.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference30 articles.
1. Carello, M., Bonansea, P., and D’Auria, M. (2014, January 8–10). Driveline Optimization for a Hybrid Electric City Vehicle to Minimize Fuel Consumption. Proceedings of the SAE 2014 World Congress & Exhibition, Detroit, MI, USA. SAE Technical Paper 2014-01-1090. 2. Pinheiro, H.D.C., Messana, A., Sisca, L., Ferraris, A., Airale, A.G., and Carello, M. (2019). Advances in Mechanism and Machine Science, Springer International Publishing. 3. Assadian, F., and Hancock, M. (2005, January 20–23). A comparison of yaw stability control strategies for the active differential. Proceedings of the IEEE International Symposium on Industrial Electronics, Dubrovnik, Croatia. 4. Siampis, E., Velenis, E., and Longo, S. (2015, January 15–18). Predictive rear wheel torque vectoring control with terminal understeer mitigation using nonlinear estimation. Proceedings of the 2015 54th IEEE Conference on Decision and Control (CDC), Osaka, Japan. 5. Siampis, E., Velenis, E., and Longo, S. (2015, January 15–17). Model Predictive torque vectoring control for electric vehicles near the limits of handling. Proceedings of the 2015 European Control Conference (ECC), Linz, Austria.
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|