DSpace Repository

Feed-forward modeling and real-time implementation of an intelligent fuzzy logic-based energy management strategy in a series–parallel hybrid electric vehicle to improve fuel economy

Show simple item record

dc.contributor.author Bansal, Hari Om
dc.contributor.author Singh, Dheerendra
dc.date.accessioned 2023-02-13T08:51:51Z
dc.date.available 2023-02-13T08:51:51Z
dc.date.issued 2020-01
dc.identifier.uri https://link.springer.com/article/10.1007/s00202-019-00914-6
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9199
dc.description.abstract A hybrid electric vehicle is powered by: the internal combustion engine and the battery-powered electric motor. These sources have specific operational characteristics, and it is necessary to match these characteristics for the efficient and smooth functioning of the vehicle. The nonlinearity and uncertainties in hybrid electric vehicle model require an intelligent controller to control the energy sharing between battery and engine. In this work, a fuzzy logic-enabled energy management strategy for the hybrid electric vehicle based on torque demand, battery state of charge and regenerative braking is designed and implemented. The proposed energy management strategy allows engine and motor to maneuver in their efficient operating regions. The designed hybrid electric vehicle and its control strategy follow the driver commands and regulations on vehicle performance and liquid fuel consumption. MATLAB/Simulink is used to carry out simulations, and then, the whole system is validated in real time on hardware-in-the-loop testing platform. This work employs an FPGA-based MicroLabBox hardware controller to validate real-time behavior. The proposed scheme results in better fuel economy, faster response and almost nil mismatch between desired and achieved vehicle speeds. en_US
dc.language.iso en en_US
dc.publisher Springer en_US
dc.subject EEE en_US
dc.subject Hybrid Electric Vehicle (HEV). en_US
dc.subject Fuel economy en_US
dc.title Feed-forward modeling and real-time implementation of an intelligent fuzzy logic-based energy management strategy in a series–parallel hybrid electric vehicle to improve fuel economy en_US
dc.type Article en_US


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account