This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Control Strategy Optimization for a Series Hybrid Vehicle
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2006 by SAE International in United States
Annotation ability available
This paper describes the development of an operating strategy for a series hybrid vehicle. The vehicle's powertrain consists of an Engine-Generator Unit (EGU), a buffer for energy storage (such as an electric battery), and a traction motor driving the wheels. The control strategy is developed so that to ensure gradual operation of the EGU along the steady-state Optimal Operating Points Line (OOP-Line) in the engine speed-torque map. The strategy functions as follows. It first determines a set-point for the state of charge of the energy buffer to minimize the probability of either discharging or overcharging it. This probability is estimated based on the statistics derived from the past history of the state of charge. Based on the difference between this set-point and estimated state of charge, the strategy calculates the power demand from the EGU which is then translated into engine torque and engine rotation speed demand so that the engine operation is maintained on the OOP-Line while delivering the requested power. The torque demand is delivered by the engine management system through the control of an engine electronic throttle while the generator voltage is adjusted to control the engine speed to the desired value. A simulation study, based on a control-oriented model of a series hybrid powertrain, is reported to illustrate the basic ideas. We also demonstrate via theoretical analysis that by periodically modulating the power output of the EGU the fuel consumption can be improved in the region where this fuel consumption is a concave function of the EGU power output. The series hybrid powertrain configuration is also relevant for fuel cells applications, and some of our considerations also extend to that case.
CitationKonev, A., Lezhnev, L., and Kolmanovsky, I., "Control Strategy Optimization for a Series Hybrid Vehicle," SAE Technical Paper 2006-01-0663, 2006, https://doi.org/10.4271/2006-01-0663.
- Affani A., Bellini A., Concari C., Franceschini G., Lorenzani E. and Tassoni C., EV Battery State of Charge: Neural Network Based Estimation, Proceedings of IEEE Electric Machines and Drives Conference, vol. 2, pp. 684-688, 2003.
- Anatone M., Cipollone R., Donati A., and Sciarretta A., Control-Oriented Modeling and Fuel Optimal Control of a Series Hybrid Bus, SAE Paper 2005-01-1163.
- Bernstein D.S. and Gilbert E.G., Optimal Periodic Control: The π-test revisited, IEEE Transactions on Automatic Control. vol. AC-25, no. 4, 1980.
- Bhangu B., Bentley P., Stone D. and Bingham C., Nonlinear Observers for Predicting State-of-Charge and State-of-Health of Lead-Acid Batteries for Hybrid-Electric Vehicles, IEEE Transactions on Vehicular Technology, vol. 54, no. 3, 2005.
- Brahma A., Guezennec Y., and Rizzoni G., Optimal Energy Management in Series Hybrid Vehicle, Proceedings of 2000 American Control Conference, Chicago, IL, pp. 60-64.
- Hochgraf C., Ryan M. and Wiegman H., Engine Control Strategy for a Series Hybrid Electric Vehicle Incorporating Load-Leveling and Computer Controlled Energy Management, SAE Paper 960230, 1996.
- Kolmanovsky I., Siverguina I., and Lygoe B., Optimization of Powertrain Operating Policies For Feasibility Assessment and Calibration: Stochastic Dynamic Programming Approach,” Proceedings of 2002 American Control Conference, pp. 1425-1430, Anchorage, AK, 8-10 May, 2002.
- Lin C., Peng H. and Grizzle J., A Stochastic Control Strategy for Hybrid Electric Vehicles,” Proceedings of 2004 American Control Conference, Boston, MA.
- Pukrushpan J.T., Peng H. and Stefanopoulou A., Control-oriented Modeling and Analysis of Fuel Cell Breathing, IEEE Control Systems Magazine, vol. 24, no. 2, pp. 30-46, 2004(a).
- Pukrushpan J.T., Stefanopoulou A. and Peng H., Control Of Fuel Cell Power Systems: Principles, Modeling, Analysis, and Feedback Design, Springer, 2004 (b).
- Rizzo G. and Pianese C., A Stochastic Approach For Optimization of Open Loop Engine Control System, Annals of Operation Research, vol. 31, pp. 545-568, 1991.
- Sun J. and Kolmanovsky I., Load Governor for Fuel Cell Oxygen Starvation Protection: A Robust Nonlinear Reference Governor Approach, IEEE Transactions on Control Systems Technology, vol. 13, no. 6, 2005.
- Vahidi A., Kolmanovsky I., and Stefanopoulou A., Constraint Management in Fuel Cell Systems: A Fast Reference Governor Approach, Proceedings of 2005 American Control Conference, Portland, Oregon.