Hierarchical control strategy with battery aging consideration for hybrid electric vehicle regenerative braking control

Regenerative braking is a key technology for hybrid electric vehicles (HEVs) to improve fuel economy, and it is a multi-objective control problem, which should ensure vehicle braking safety, recover more energy, and protect components from aging. As is known, battery is the most sensitive component in hybrid powertrain, so a large recover current can cause damage to the battery and reduce its life. However, the damage to is usually ignored in regenerative braking. Therefore, this paper proposed a hierarchical control strategy with battery aging consideration to solve the problem. In the up-level controller, the control targets are to recover more energy and minimize aging of the battery in general braking mode, and ensuring the vehicle braking safety in emergency braking mode at the same time. The low-level controller receives the commands of the up-level controller, and controls the pneumatic braking system and the electric motor (EM). The constraints of maximum EM torque and maximum battery charging power are set to protect the EM and the battery. Simulation tests are designed to indicate the effects of regenerative braking on battery aging and the control effectiveness of the proposed method, and controller-in-the-loop tests are carried out to verify the real-time calculation performance.

[1]  Liang Li,et al.  Transient switching control strategy from regenerative braking to anti-lock braking with a semi-brake-by-wire system , 2016 .

[2]  James Marco,et al.  On the possibility of extending the lifetime of lithium-ion batteries through optimal V2G facilitated by an integrated vehicle and smart-grid system , 2017 .

[3]  Chris Mi,et al.  Active-charging based powertrain control in series hybrid electric vehicles for efficiency improvement and battery lifetime extension , 2014 .

[4]  Rui Esteves Araujo,et al.  Study on the combined influence of battery models and sizing strategy for hybrid and battery-based electric vehicles , 2017 .

[5]  Kai He,et al.  AMT downshifting strategy design of HEV during regenerative braking process for energy conservation , 2016 .

[6]  Sousso Kelouwani,et al.  Long-term assessment of economic plug-in hybrid electric vehicle battery lifetime degradation management through near optimal fuel cell load sharing , 2016 .

[7]  Wei Li,et al.  Fuzzy terminal sliding mode control for extracting maximum marine current energy , 2015 .

[8]  P. Venkatesh,et al.  Simultaneous coordination of distinct plug-in Hybrid Electric Vehicle charging stations: A modified Particle Swarm Optimization approach , 2017 .

[9]  Liang Li,et al.  Fuel consumption optimization for smart hybrid electric vehicle during a car-following process , 2017 .

[10]  Hosam K. Fathy,et al.  Tradeoffs between battery energy capacity and stochastic optimal power management in plug-in hybrid electric vehicles , 2010 .

[11]  Joeri Van Mierlo,et al.  Influence analysis of static and dynamic fast-charging current profiles on ageing performance of commercial lithium-ion batteries , 2017 .

[12]  Yang Yang,et al.  Design and Simulation of Pressure Coordinated Control System for Hybrid Vehicle Regenerative Braking System , 2014 .

[13]  Zhonghao Rao,et al.  Experimental investigation on thermal management of electric vehicle battery with heat pipe , 2013 .

[14]  Xiwang Li,et al.  Multi-objective optimization for thermal mass model predictive control in small and medium size commercial buildings under summer weather conditions , 2016 .

[15]  Zhiguang Zhou,et al.  Integrated control of electromechanical braking and regenerative braking in plug-in hybrid electric vehicles , 2012 .

[16]  Hyunsoo Kim,et al.  Development of Brake System and Regenerative Braking Cooperative Control Algorithm for Automatic-Transmission-Based Hybrid Electric Vehicles , 2015, IEEE Transactions on Vehicular Technology.

[17]  Chao Yang,et al.  Model Predictive Control-based Efficient Energy Recovery Control Strategy for Regenerative Braking System of Hybrid Electric Bus , 2016 .

[18]  Junzhi Zhang,et al.  Integrated control of braking energy regeneration and pneumatic anti-lock braking , 2010 .

[19]  Zechang Sun,et al.  State of charge estimation for lithium-ion pouch batteries based on stress measurement , 2017 .

[20]  Hosam K. Fathy,et al.  Plug-in hybrid electric vehicle charge pattern optimization for energy cost and battery longevity , 2011 .

[21]  Hans B. Pacejka,et al.  THE MAGIC FORMULA TYRE MODEL , 1991 .

[22]  A. Eddahech,et al.  Performance comparison of four lithium–ion battery technologies under calendar aging , 2015 .

[23]  M. Pecht,et al.  Cycle life testing and modeling of graphite/LiCoO 2 cells under different state of charge ranges , 2016 .