Switching Controller Design for Hybrid Electric Vehicles

This paper addresses switching controller design for hybrid electric vehicle systems. The merit of using switching control scheme is that sub-controllers specialized for various driving conditions improve the fuel efficiency. A simultaneous perturbation stochastic approximation (SPSA) based method is used to optimize the design parameters of the switching controller. The design method is applied to the JSAE-SICE benchmark problem which are developed using GT-SUITE of Gamma Technologies, Inc. and integrated with Simulink / MATLAB. Experimental results illustrate that the proposed controller can achieve almost 47% improvement in fuel efficiency, compared with the sample controller of the benchmark problem.

[1]  Yuji Yasui,et al.  Development of Energy Management of Hybrid Electric Vehicle for Improving Fuel Consumption Via Sequential Approximate Optimization , 2013 .

[2]  Shun-ichi Azuma,et al.  Controller Design for Optimizing Fuel Consumption of Hybrid Electric Vehicles , 2013 .

[3]  Lino Guzzella,et al.  Optimal control of parallel hybrid electric vehicles , 2004, IEEE Transactions on Control Systems Technology.

[4]  Y. Yasui,et al.  JSAE-SICE Benchmark problem2: Fuel Consumption Optimization of Commuter Vehicle Using Hybrid Powertrain , 2012, Proceedings of the 10th World Congress on Intelligent Control and Automation.

[5]  Thierry-Marie Guerra,et al.  Control of a parallel hybrid powertrain: optimal control , 2004, IEEE Transactions on Vehicular Technology.

[6]  Günther R. Raidl,et al.  Applying (Hybrid) Metaheuristics to Fuel Consumption Optimization of Hybrid Electric Vehicles , 2012, EvoApplications.

[7]  J. Spall.  Multivariate stochastic approximation using a simultaneous perturbation gradient approximation , 1992 .

[8]  W. Gao,et al.  Design optimization of a parallel hybrid electric powertrain , 2005, 2005 IEEE Vehicle Power and Propulsion Conference.

[9]  Shi-Yin Qin,et al.  Concurrent Optimization for Parameters of Powertrain and Control System of Hybrid Electric Vehicle Based on Multi-Objective Genetic Algorithms , 2006, 2006 SICE-ICASE International Joint Conference.

[10]  Maarten Steinbuch,et al.  Optimal Control of a Mechanical Hybrid Powertrain , 2012, IEEE Transactions on Vehicular Technology.

[11]  Shun-ichi Azuma,et al.  Model free tuning of variable state of charge target of hybrid electric vehicles , 2013 .