A Simple Technique for Optimal Selection of Degree of Hybridization (DOH) in Parallel Passenger Hybrid Cars

In this paper, a simple but efficient Non-dominated Sorting Genetic Algorithm (NSGA) II based technique is proposed for optimizing the Degree of Hybridization (DOH) in parallel passenger hybrid cars. The authors' objective is to improve performance, maximize fuel economy and at the same time, minimize mass and emissions as much as possible, by optimal selection of DOH. The NSGA-II, which is a multi-objective optimization algorithm, is applied to optimize this multiple objective problem. The ADvanced VehIcle SimulatOR (ADVISOR) software is used as simulation tool. To validate high efficiency of proposed methodology, necessary simulations have been carried out on a small-size test car. The results indicates that the proposed methodology is very fast and efficient and can be well applied to any other types of Hybrid Electric Vehicles (HEVs).
U radu je predložena jednostavna i efikasna metoda zasnovana na nedominirano-sortirajućem genetičkom algoritmu (NSGA) II u svrhu optimiranja stupnja hibridizacije (DOH) u paralelnim putničkim hibridnim automobilima. Cilj je unaprijediti performanse, maksimizirati ekonomičnost goriva te istovremeno minimizirati emisiju koliko god je moguće uz optimalni odabir DOH. NSGA-II algoritam, koji spada u višekriterijske optimizacijske algoritme, korišten je za optimiranje problema s više ciljeva. Napredni simulator vozila (ADVISOR softver) korišten je kao simulacijski alat. Simulacije su provedene na umanjenom testnom vozilu kako bi se validirala visoka efikasnost predložene metodologije. Rezultati ukazuju da je predložena metoda vrlo brza i efikasna te ju je moguće primijeniti i na bilo koji drugi tip hibridnog električnog vozila (HEV).