Thrust 1:Optimal sizing and control for the hybrid powertrains of ground vehicles

Optimal control theories, including dynamic programming, Pontryagin's minimum principle, and the combine optimization for sizing and control have been applied in hybrid powertrain optimal design and control. However, the further investigations for adaptive or learning-based control and the efficient modeling and computation for the combined optimal design for hybrid powertrain are deserved. 

 

References:

1. Zou, Y., Sun, F-C.,Zhang, C-N. and Li, J.Q. Optimal energy management strategy for hybrid electric tracked vehicles. Int. J. Vehicle Design, 2013; 58(2/3/4): 307–324.

2. Zou Y, Sun F, Hu X, Guzzella L, Peng H. Combined Optimal Sizing and Control for a Hybrid Tracked Vehicle. Energies. 2012; 5(11):4697-4710.

3. Yuan Z, Teng L, Fengchun S, Peng H. Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle. Energies. 2013; 6(4):2305-2318.

4. Yuan Zou, Dong-ge Li, and Xiao-song Hu. Optimal Sizing and Control Strategy Design for Heavy Hybrid Electric Truck. Mathematical Problems in Engineering. 2012,Article ID 404073, 15 pages, 2012. doi:10.1155/2012/404073.

5. ZOU Yuan, CHEN Rui, HOU Shijie, HU Xiaosong. Energy Management Strategy for Hybrid Electric Tracked Vehicle Based on Stochastic Dynamic Programming (In Chinese). Journal of Mechanical Engineering, 2013; 48(14): 91-96.

6. Shi-Jie Hou, Yuan Zou(Corresponding author), Rui Chen. Modeling and Control Optimization of a Hybrid Electric Truck [J]. Transactions of Beijing Institute of Technology, 2012, Suppl.

7. Yuan Zou,Hou Shijie, etc. Hybrid electric commercial truck energy management optimization based on dynamic programming [J]. Automotive Engineering, 2012, 34(8): 663-668.

8. Yuan ZOU,Chengning ZHANG,Fengchun SUN,Jingbo WU. Power control of dual-motor electric drive for tracked vehicles. Chinese Frontier of Mechanical Engineering. 2010,5(1): 67-72

9. ZOU Yuan, GAO Wei, HOU Shi-jie, CHEN Rui, LI Jun-qiu. System-level modeling and real-time simulation for hybrid tracked vehicle. Transaction of Beijing Institute of Technology, 2013, 33(1): 31-36.

Thrust 2:Lithium-ion battery modeling and identification

The understanding for the lithium-ion battery dynamics plays an important role in electric vehicles. The power capacity and reliability constrain the power supply from battery. Lithium-ion battery is often taken as ‘grey box’ or ‘black box’. Modeling and identification is a promising way to find out more information from the history data from the battery testing.

 

References:

1. HU Xiao-song, SUN Feng-chun, Zou Yuan(Corresponding author). Online model identification of lithium-ion battery for electric vehicles [J]. Journal of Central South University of Technology,2011,18(5):1525-1530.

2. Xiao song Hu, Fengchun Sun, Yuan Zou. Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer [J]. Energies 2010, 3, 1586-1603.

3. Fengchun Sun, Xiaosong Hu, Yuan Zou, Siguang Li. Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles [J]. Energy, 2011, 36(5):3531-3540.

4. HU Xiaosong, SUN Fengchun, Zou Yuan. SOC Distribution-Based Modeling for a Lithium-Ion Battery for Electric Vehicles using Numerical Optimization [J]. Journal of Harbin Institute of Technology (New Series).2011,18(5):49-54.

5. HU Xiaosong, SUN Fengchun, Zou Yuan. Modeling the Dynamic Behavior of a Lithium-ion Battery for Electric Vehicles Using Numerical Optimization [J]. Journal of Beijing Institute of Technology, 2011, 20(1):60-64.

 

Thrust 3: Connected & Electrified vehicle operation and coupling with grid and transportation

Electrified vehicles rsequire the infrastructure and on-board electricity storage device normally. When large-scale electrified vehicles are applied, some new characteristics and dynamic process will be incurred. This comlicated dynamics consist of multiple time scale super system, such as electric cars in the tranportations, metro systems and railway system. More investigation into the system level efficiency analysis and advacne control is required.

Connected & Electrified vehicle is promising to improve the system safety and efficiency of the automove-based transporation system and thus deserves the investigation.

References:

1. Yuan Zou,Shouyang Wei,Fengchun Sun. Large-scale deployment of electric taxis in Beijing: A real-world analysis [J]. Energy, 2016, 100, 25-29.

2. Zou Yuan, Fu Yi-long. Operation characteristic visual simulation for metro train in the tunnel under the river [J]. Journal of system simulation, 2008, (8): 2182~2219.