Neural network based power management of hydraulic hybrid vehicles
Author:
Affiliation:
1. Maha Fluid Power Research Center, Purdue University, West Lafayette, IN, USA
Funder
Graduate Automotive Technology Education (GATE) program DOE
Publisher
River Publishers
Subject
General Physics and Astronomy,Mechanical Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/14399776.2016.1232117
Reference9 articles.
1. DYNAMIC PROGRAMMING AND LAGRANGE MULTIPLIERS
2. Buchwald, P.et al. 1979. Improvement of a citybus fuel economy using a hydraulic hybrid propulsion system – a theoretical and experimental study.Proceedings of the 1979 automotive engineering congress and exposition, 26 February–2 March 1979, Detroit, MI, USA. SAE paper 790305.
3. Johri, R., Baseley, S., and Filipi, Z., 2011. Simultaneous optimization of supervisory control and gear shift logic for a parallel hydraulic hybrid refuse truck using stochastic dynamic programming.ASME/bath symposium on fluid power and motion control, Arlington, VI, USA.10.1115/DSCC2011-6172
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