Computationally efficient velocity and power split control of hybrid electric vehicles

Uebel, Stephan; Murgovski, Nikolce; Tempelhahn, Conny; Bäker, Bernard

doi:10.1109/ccta.2017.8062688

Cited by 3 publications

(1 citation statement)

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“…A salient aspect of indirect optimization methods is that when they converge accurately, they result in high-resolution solutions, which is quite instrumental for validation and/or training methods that rely on machine learning algorithms to approximate optimal trajectories [43]. Superior speed performance is achievable for some problems when indirect methods are used [44].…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Optimal Trajectory Design with Multiple Operation Modes of Propulsion System, Part 1

Taheri¹,

Junkins²,

Kolmanovsky³

et al. 2019

Preprint

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Efficient performance of a number of engineering systems is achieved through different modes of operation -yielding systems described as "hybrid", containing both real-valued and discrete decision variables. Prominent examples of such systems, in space applications, could be spacecraft equipped with 1) a variable-I sp , variable-thrust engine or 2) multiple engines each capable of switching on/off independently. To alleviate the challenges that arise when an indirect optimization method is used, a new framework -Composite Smooth Control (CSC)is proposed that seeks smoothness over the entire spectrum of distinct control inputs. A salient aftermath of the application of the CSC framework is that the original multi-point boundary-value problem can be treated as a two-point boundary-value problem with smooth, differentiable control inputs; the latter is notably easier to solve, yet can be made to accurately approximate the former hybrid problem. The utility of the CSC framework is demonstrated through a

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Section: Introductionmentioning

confidence: 99%