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Predictive Boundary Management Control of a Hybrid Powertrain

[+] Author Affiliations
Jie Yang, Guoming G. Zhu

Michigan State University, East Lansing, MI

Paper No. DSCC2014-6009, pp. V002T20A002; 7 pages
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4619-3
  • Copyright © 2014 by ASME


Hybrid Electric Vehicle (HEV) is capable of improving fuel economy with reduced emissions over traditional vehicles powered by the internal combustion engine alone. However the HEV durability is significantly limited by the battery useful life; and the battery life could be significantly reduced if it was operated over its allowed charging or discharging limits, which could occur especially at extremely low battery temperatures, leading to permanent battery damage and reduced battery life. In order to extend the battery life, this paper proposed a battery boundary management control strategy based upon the predicted desired torque to proactively make the engine power available to reduce future battery over-discharging. The proposed control strategy was validated in simulations and its performance was compared with the baseline control strategy under US06, and other four typical city and highway driving cycles. The simulation results show that the proposed control strategy is very effective when the battery temperature is under zero Celsius degree, and the over-discharged power is reduced more than 65% under aggressive US06 and ARB02 driving cycles, 45% under highway and city FTP and city NYCC driving cycles, and 30% under highway IM240 driving cycle, respectively.

Copyright © 2014 by ASME



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