2017
DOI: 10.1016/j.apenergy.2016.07.020
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A pseudospectral method for solving optimal control problem of a hybrid tracked vehicle

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Cited by 37 publications
(16 citation statements)
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“…This method has the advantages of high precision, low sensitivity to an initial value, and fast convergence speed, and is convenient to deal with terminal constraint problems. In [29,30], the calculation process of the PM algorithm has been introduced in detail, and has been successfully applied to the energy management of hybrid electric vehicles. The PM algorithm can obtain the same global optimal solution as dynamic programming (DP) in a shorter time.…”
Section: A Upper Layer Optimizationmentioning
confidence: 99%
“…This method has the advantages of high precision, low sensitivity to an initial value, and fast convergence speed, and is convenient to deal with terminal constraint problems. In [29,30], the calculation process of the PM algorithm has been introduced in detail, and has been successfully applied to the energy management of hybrid electric vehicles. The PM algorithm can obtain the same global optimal solution as dynamic programming (DP) in a shorter time.…”
Section: A Upper Layer Optimizationmentioning
confidence: 99%
“…This was shown to be computationally more efficient than a standard DP approach. Improvements in solution accuracy are possible [13]. The authors of [14] presented a formulation of the eco-driving problem with particular emphasis on the high-fidelity modelling of both the vehicle and the road.…”
Section: Introductionmentioning
confidence: 99%
“…As a typical direct method belonging to nonlinear programming (NLP)solution, the pseudo-spectral method (PM) has been increasingly used for numerical solving of global optimal control problems for various dynamic systems [28][29]. The PM uses the orthogonal matching point to discretize the continuous optimal control problem, and approximates the state and control variables through global interpolation polynomial, thus transforming the problem into an NLP problem.…”
Section: Introductionmentioning
confidence: 99%