Development and Evaluation of Intelligent Energy Management Strategies for Plug-in Hybrid Electric Vehicles

In this study, we proposed an intelligent energy management strategy for plug-in hybrid electric vehicles. At the trip level, the strategy takes into account a priori knowledge of vehicle location, roadway characteristics, and real-time traffic information on the travel route from intelligent transportation system technologies in generating synthesized velocity trajectory for the trip. The synthesized velocity trajectory is then used to determine charge-depleting control that is formulated as a mixed integer linear programming to minimize the total fuel consumption for the trip. The strategy can be extended to optimize fuel consumption at the tour level if a pre-planned travel itinerary for the tour and the information about available battery recharging opportunities at intermediate stops in the tour are available. The effectiveness of the proposed strategy, both for the trip-based and tour-based controls, was evaluated against the existing binary mode energy management strategy using a real-world example trip/tour in Southern California. The evaluation results show that the fuel savings of the proposed strategy over the binary mode strategy are around 10-15%.

[1]  Erik van Zwet,et al.  A simple and effective method for predicting travel times on freeways , 2004, IEEE Transactions on Intelligent Transportation Systems.

[2]  Mashrur Chowdhury,et al.  An energy optimization strategy for power-split drivetrain plug-in hybrid electric vehicles , 2012 .

[3]  Chen Zhang,et al.  Role of Trip Information Preview in Fuel Economy of Plug-In Hybrid Vehicles , 2009 .

[4]  Yaoyu Li,et al.  Power management of plug-in hybrid electric vehicles using neural network based trip modeling , 2009, 2009 American Control Conference.

[5]  Guillermo R. Bossio,et al.  Optimization of power management in an hybrid electric vehicle using dynamic programming , 2006, Math. Comput. Simul..

[6]  Huei Peng,et al.  Modeling and Control of a Power-Split Hybrid Vehicle , 2008, IEEE Transactions on Control Systems Technology.

[7]  Giorgio Rizzoni,et al.  A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[8]  Alexandre M. Bayen,et al.  Traffic flow reconstruction using mobile sensors and loop detector data , 2007 .

[9]  Robert C. DeVault.  “Just-in-Time” Battery Charge Depletion Control for PHEVs and E-REVs for Maximum Battery Life , 2009 .

[10]  Jie Lin,et al.  Estimating Regional Air Quality Vehicle Emission Inventories: Constructing Robust Driving Cycles , 2003, Transp. Sci..

[11]  G. Rizzoni,et al.  Effects of different PHEV control strategies on vehicle performance , 2009, 2009 American Control Conference.

[12]  Lieuwe Krol.  The reconstruction of vehicle trajectories with dynamic macroscopic data , 2009 .

[13]  Huei Peng,et al.  Power management strategy for a parallel hybrid electric truck , 2003, IEEE Trans. Control. Syst. Technol..

[14]  Matthew J. Barth,et al.  Eco-Routing Navigation System Based on Multisource Historical and Real-Time Traffic Information , 2012, IEEE Transactions on Intelligent Transportation Systems.

[15]  Pravin Varaiya,et al.  Travel-Time Reliability as a Measure of Service , 2003 .

[16]  Matthew Barth,et al.  Using GPS Technology to Relate Macroscopic and Microscopic Traffic Parameters , 1996 .

[17]  Chen Zhang,et al.  Real-time optimal control of plug-in hybrid vehicles with trip preview , 2010, Proceedings of the 2010 American Control Conference.

[18]  D. Karbowski,et al.  PLUG-IN VEHICLE CONTROL STRATEGY : FROM GLOBAL OPTIMIZATION TO REAL-TIME APPLICATION , 2010 .

[19]  Mashrur Chowdhury,et al.  Forward power-train energy management modeling for assessing benefits of integrating predictive traffic data into plug-in-hybrid electric vehicles , 2012 .

[20]  Daiheng Ni,et al.  Trajectory Reconstruction for Travel Time Estimation , 2008, J. Intell. Transp. Syst..

[21]  I. Kolmanovsky,et al.  Optimization of complex powertrain systems for fuel economy and emissions , 1999, Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328).

[22]  Zoran Filipi,et al.  Modeling and Analysis of the Toyota Hybrid System , 2005 .

[23]  J. V. van Lint,et al.  Improving a Travel-Time Estimation Algorithm by Using Dual Loop Detectors , 2003 .