Yapay Zeka Hızlı Bakış & Çıkarımlar
AI InsightFinally, ECMS is enhanced by novel method based on predictive information to anticipate upcoming road topology in order to fully benefit either the free recuperation energy over long downhill road sections or via pre-charging strategy against uphill road sections
📌 3 Maddede Bu Makale
Abstract
The possibility to distribute the traction power in Hybrid Electric Vehicles powertrain over different prime movers and energy recoverability via recuperative braking as well as buffering the energy on rechargeable batteries, lead to the question of how electrical, mechanical or chemical energy should flow among various hybrid components of the powertrain. This optimization problem, mostly called energy management of hybrid electric vehicles aims to find the minimum consumed fuel energy flow, in other words fuel consumption over the entire trip. This study describes the application of theoretical global optimization method called Dynamic Programming (DP) and a practical approach substitute, namely Equivalent Consumption Minimization Strategy (ECMS) to a parallel hybrid powertrain energy management problem and their virtual tests in various drive-cycles. The computational burden of DP has been relaxed by ECMS approach and sub-optimal behaviour is rather comparable to global optimal behaviour. Finally, ECMS is enhanced by novel method based on predictive information to anticipate upcoming road topology in order to fully benefit either the free recuperation energy over long downhill road sections or via pre-charging strategy against uphill road sections