Fuzzy Based Controller Design for Parallel Hybrid Electric Vehicle An Approach to Fuel Consumption and Emission Reduction
سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 481
فایل این مقاله در 10 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
KBEI02_178
تاریخ نمایه سازی: 5 بهمن 1395
چکیده مقاله:
Reduction of greenhouse gas emission and fuel consumption as one of the main goals of automotive industry leading to the development hybrid vehicles. The objective of this paper is to investigate the energy management system and control strategies effect on fuel consumption, air pollution and performance of hybrid vehicles in various driving cycles. In this paper a GA-based optimized parallel HEV is considered. And so simulation performed due to Matlab and in the Advisor enviroment. Also a new fuzzy-based controller designed and so various strategies in different driving cycles investigated with an approach to fuel consumption and emission reduction. The simulation procedure had been carried out as a comparison problem to investigate the partnership for a new generation of vehicles (PNGV) and its effects on performance of the vehicle. The simulation results represent that if the PNGV terms not regarded in the parallel HEV performance simulations, with the proposed controller, fuel consumption and emission amount reduced saliently, however, acceleration and power of gradeability of vehicle reduced too. But with effort to observe the PNGV terms, power of vehicle and its acceleration could be improved. Hence the efficiency of the HEV rised reciprocally.
کلیدواژه ها:
control strategy ، fuel consumption and emission reduction ، fuzzy controller ، parallel HEV ، optimized design ، PNGV
نویسندگان
Amir Behzadpour
Electrical Engineering Department Islamic Azad University Gonabad, Iran
Hossein Eliasi
Electrical Engineering Faculty University of Birjand Birjand, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :