This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Developing a Model Predictive Control-Based Algorithm for Energy Management System of the Catenary-Based Electric Truck
Technical Paper
2016-01-2359
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
Although the cost-saving and good environmental impacts are the benefits that make Electric Vehicles (EVs) popular, these advantages are significantly influenced by the cost of battery replacement over the vehicle lifetime. After several charging and discharging cycles, the battery is subjected to energy and power degradation which affects the performance and efficiency of the vehicle. In addition to battery replacement cost, the electricity cost being paid by drivers is another key factor in selecting the EVs. An Energy Management System (EMS) with Model Predictive Control-based (MPC) algorithm is presented for a specific case of heavy-duty EV. Such EV draws its energy from the grid via catenary in addition to the on-board battery. Dynamic model of the vehicle will be defined by State Space Equations (SSE). The simulation results for MPC-based EMS of a Catenary-based Range-extended Electric Vehicle (CREV) is presented, the control aim is to manipulate the power flow from the grid in order to minimize the cost of purchased electricity from grid and improve the life time of the battery will be presented.
Authors
Citation
Olia, K., Shahverdi, M., Mazzola, M., and Sherif, A., "Developing a Model Predictive Control-Based Algorithm for Energy Management System of the Catenary-Based Electric Truck," SAE Technical Paper 2016-01-2359, 2016, https://doi.org/10.4271/2016-01-2359.Also In
References
- Lowe M. , Ayee G. and Gereffi G. Hybrid Drivetrains for Medium- and Heavy-Duty Trucks Center on Globalization, Governance & Competitiveness, Duke University 2009
- Boyce C. ATA Releases: American Trucking Trends 2008 ' 2009 American Trucking Associations 2008
- Thiruvengadam A. , Pradhan S. , Thiruvengadam P. , Besch M. , Carder D. and Delgado O. Heavy-Duty Vehicle Diesel Engine Efficiency Evaluation and Energy Audit Center for Alternative Fuels, Engines & Emissions West Virginia University Morgantown, WV Oct. 2014
- Vehicle Technologies Program National Renewable Energy Laboratory (NREL) U.S. Department of Energy October 2011
- Linden D. and B. R. Handbook of batteries 3rd New York McGraw-Hill 2001
- Vetter J. , Novák P. , Wagner M. , Veit C. , Möller K.-C. , Besenhard J. , Winter M. , Wohlfahrt-Mehrens M. , Vogler C. and Hammouche A. Ageing mechanisms in lithium-ion batteries Power Sources 147 1-2 269 281 Sep. 2005
- A.G R. Recent developments and likely advances in lithium rechargeable batteries Journal of Power Sources 136 285 289 2004
- Fellner J. , Loeber G. , Vukson S. and Riepenhoff C. Lithiumiontesting for spacecraft applications Journal of Power Sources 119-121 911 913 Jun. 2003
- Wang X. , Sone Y. and kuwajima S. Effect of operation conditions on simulated low-earth orbit cycle-life testing of commercial lithium-ion polymer cells Journal of Power Sources 142 1/2 313 322 Mar. 2005
- Bradley T. H. , Wood E. and Alexander M. Investigation of battery end-of-life conditions for plug-in hybrid electric vehicles Power Sources 196 11 5147 5154 Jun. 2011
- Comparing Energy Costs per Mile for Electric and Gasoline-Fueled Vehicles U.S. Department of Energy, Idaho National Laboratory Idaho Falls January 2011
- Masters A. , Wishart J. and Francfort J. Tacoma Power/AVTA PHEV Demand and Energy Cost Demonstration -Analysis Report U.S. Department of Energy, Idaho National Laboratory Idaho Falls May 2010
- Smart J. , Davies J. , Shirk M. , Quinn C. and Kurani K. S. Electricity Demand of PHEVs Operated by Private Households and Commercial Fleets: Effects of Driving and Charging Behavior The 25th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium & Exhibition Shenzhen, China November 2010
- Chiasson J. and Vairamohan B. Estimating the State of Charge of a Battery IEEE Transactions on control systems technology 13 3 465 470 2005
- Mosca E. Model-Based Predictive Control Control System, Robotics, and Automation 11
- Cannon M. Mark Cannon's teaching material July 2014 http://www.eng.ox.ac.uk/~conmrc/mpc/mpc1-2.pdf 6 Augest 2016
- Enders W. Stationary Time-Series Models Applied Econometric Time Series (Second ed.) New York Wiley 2003 48 107
- Whittle P. Hypothesis testing in time series analysis Uppsala Almqvist & Wiksells boktr. 1951
- Box G. , Jenkins G. M. and Reinsel G. C. Time Series Analysis, Forecasting, and Control Wiley 2008
- Time Series Forecasting System SAS Institute https://support.sas.com/documentation/cdl/en/etsug/63939/HTML/default/viewer.htm#etsug_tffordet_sect016.htm 21 August 2016
- Introduction to ARIMA http://people.duke.edu/~rnau/411arim.htm#arima010 21 August 2016
- Kalman R. A New Approach to Linear Filtering and Prediction Problems ASME-Journal of Basic Engineering 8 35 45 1960
- J. B. R. and Mayne D. Q. Model Predictive Control:Theory and Design Madison, Wisconsin Nob Hill Publishing LLC 2015
- Maciejowski J. Control Group, Cambridge University Department of Engineering 2014 07 August 2016
- EV_Rate San Diego Gas & Electric 1 January 2016 http://www.sdge.com/clean-energy/ev-rates 1 May 2016
- Tiered Rates San Diego Gas & Electric Company 01 September 2015 http://www.sdge.com/tiered-rates August 21 2016
- Shahverdi M. , Moazzola M. , Abdelwahed S. , Doude M. and Zhu D. MPC-based power management system for a plug-in hybrid electric vehicle for relaxing battery cycling IEEE iTEC Novi, MI 2016