| ADAPTIVE CONTROL STRATEGY EXTRACTED FROM DYNAMIC
PROGRAMMING AND COMBINED WITH DRIVING PATTERN
RECOGNITION FOR SPHEB |
Xinyou Lin1, 2
, Hailin Li3 |
1Fuzhou University
2Fujian Province University
3West Virginia University |
|
|
|
|
|
|
| |
| ABSTRACT |
|
An appropriate control strategy can play an important role in further improving the fuel economy performance
of hybrid electric vehicle (HEV). This research developed a novel adaptive control strategy to achieve optimal power
distribution for a series-parallel hybrid electric bus (SPHEB) to adapt driving pattern instantaneously. First, a methodology of
extracting mode transition control and power distribution strategy from dynamic programming (DP) solution is proposed for
the development of the hierarchical energy management strategy. A SPHEB energy management problem under the Chinese
typical bus driving schedule at urban district (CTBDS_UD) is investigated as a case study. Second, an approach of driving
pattern recognition (DPR) module is developed. For adaptive learning, four typical driving patterns are selected as the
database of driving condition and using the extraction method described above to acquire optimal control strategies for four
driving patterns. Third, a framework of adaptive control strategy has been proposed based on the extracted hierarchical energy
management strategy from DP and combined with DPR. Finally, the simulation results demonstrate the proposed adaptive
strategy can make power distribution proper adjustments in real time and be capable of improving significantly the fuel
efficiency of the SPHEB. |
| Key Words:
Hybrid electric vehicle, Adaptive control strategy, Driving pattern recognition, Dynamic programming,
Multivariable nonlinear regression, Learning vector quantization |
|
|
|
Corresponding Author.
Xinyou Lin , Email. 
Preview
Full text via DOI
Download Citation 
Print 
