Power Flow Management in HEV using Adaptive Neuro-Fuzzy Controller
- Resource Type
- Conference
- Authors
- Srivastava, Swapnil; Maurya, Sanjay Kumar
- Source
- 2022 IEEE Students Conference on Engineering and Systems (SCES) Engineering and Systems (SCES), 2022 IEEE Students Conference on. :1-6 Jul, 2022
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Simulation
Power distribution
Fuel economy
DC motors
Batteries
State of charge
Energy management systems
Energy Management System (EMS)
Adaptive neural fuzzy interference system (ANFIS)
Hybrid Electric Vehicle (HEV)
fuel economy component
formatting
style
styling
- Language
The effective power distribution between electrical and mechanical system is always a challenge for control engineers. This paper presents a controller design based on an Adaptive neural fuzzy inference system (ANFIS) for improving the fuel economy. The Energy Management System (EMS) ensures effective power distribution between Internal Combustion Engine (ICE) and Electric Motor (EM). The ANFIS Controller is trained for controlling the on-off of ICE, EM and generator on the basis of value of speed, SOC and engine rpm. The simulation results show the better fuel economy and the battery's state of charge (SOC), thereby improving the battery life cycle. The EMS showed good regenerative capabilities.