Predictive-Equivalent Consumption Minimization Strategy for Energy Management of A Parallel Hybrid Vehicle for Optimal Recuperation

Paralel Hibrit Elektrikli Aracın, Optimal Reküperatif Frenleme için Öngörülü-Eşdeğer Yakit Tüketimi Minimizasyonu Startejisi ile Enerji Yöntemi

Abstract

The cost of routing vehicles represents an important component of many transportation and distribution costs in a logistics system. The typical vehicle routing problem involves in designing a set of minimumcost routes for a fleet of vehicle. The vehicle routing problem with time windows is a generalization of the vehicle routing problem where the service of a customer can begin within the time window defined by the earliest and the latest times when the customer will permit the start of service. In this study, The Vehicle Routing problem that root of the logistic systems is handled as Time Window Vehicle Routing Problem to obtain the routes of the vehicles that are used by the Arçelik Authorized Service. These vehicles distribute the products which were sold to Sincan and Etimesgut Regions in Ankara. Recommended model was structured and solved with real datas using Mix Integer Programming. With respect to the results the improvings are shown and the optimal routes are obtained. By thematematical model, the customers' demands, that authorized service provided with 761.399 km, could be also provided. The situation which the total distance could be reduced as 67.90% was demonstrated. The routes which could be provided on time and costed minimum was revealed

Özet

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 wordsfuel 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.