An iterative dynamic programming/convex optimization procedure for optimal sizing and energy management of PHEVs

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• 作者：Mitra Pourabdollah ^{mitrap@chalmers.se" class="auth_mail" title="E-mail the corresponding author} ; Nikolce Murgovski ^{nikolce.murgovski@chalmers.se" class="auth_mail" title="E-mail the corresponding author} ; Anders Grauers ^{anders.grauers@chalmers.se" class="auth_mail" title="E-mail the corresponding author} ; Bo Egardt ^{bo.egardt@chalmers.se" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Hybrid electric vehicles ; Optimal sizing ; Driving cycles ; Convex optimization ; Dynamic programming ; Gear shifting ; Engine on-off
• 刊名：IFAC-PapersOnLine
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：47
• 期：3
• 页码：6606-6611
• 全文大小：456 K

文摘

This paper proposes a time-efficient method for sub-optimal design of a plug-in hybrid electric vehicle with a parallel powertrain topology. The method finds the optimal design of the vehicle by iteratively using dynamic programming (DP) and convex optimization to minimize sum of operational and component costs over a given driving cycle. In particular, DP is used to optimize energy management, gear shifting and engine on-off for given component sizes, and convex optimization is used to optimize energy management and component sizes using the gear shifting and engine on-off strategies obtained by DP. Next, DP is re-optimized with the component sizes obtained by convex optimization, and the procedure is repeated until the component sizes converge. The result of this iterative method is compared by using DP on a grid of possible component sizes. It is shown that the iterative method gives a result very close to the global optimum in a comparably short time.