Power Split Strategy Using Cascaded Fuzzy Control in a Hybrid Electric Vehicle

In the present scenario, the research outcomes related to hybrid electric vehicles are highly dominating the entire novelty sector. Initially, the long-term operation of electric vehicles was found to be ineffective in the case of electric vehicles (EVs), and then only the hybrid concept was encapsulated. Now, it is a real challenge to control the power split strategy for an ideal run and an economical run as well. Many papers explored and investigated with a few novel initiatives indeed. In this paper, one of the most unique analyses has been discussed by considering rotational inertia and angular displacement of the wheel in the case of running on a battery only. On the other hand, based on the battery state of charge (SOC), battery ampere, as well as power splitting takes place between the battery and the internal combustion engine. The entire concept is described in this paper using a type 1 fuzzy logic controller (FLC) by incorporating Triplets as membership functions (MFs). In this work, the centre of area (COA) method is used for defuzzification. In this work, cascaded fuzzy is introduced as an Artificial Intelligence approach and applied in hybrid electric vehicles for intelligent optimum power splitting strategic planning. The study is theoretically constructed and validated using a few simulation-based results.

Institutions

Publication Details

Journal
Fuzzy Sets and Systems
Published
2024-12-18
DOI
https://doi.org/10.71602/tfss.2026.1193875
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Power Split Strategy Using Cascaded Fuzzy Control in a Hybrid Electric Vehicle

Fuzzy Sets and Systems
Geochemistry and Geologic Mapping
article

Power Split Strategy Using Cascaded Fuzzy Control in a Hybrid Electric Vehicle

article en

Abstract

In the present scenario, the research outcomes related to hybrid electric vehicles are highly dominating the entire novelty sector. Initially, the long-term operation of electric vehicles was found to be ineffective in the case of electric vehicles (EVs), and then only the hybrid concept was encapsulated. Now, it is a real challenge to control the power split strategy for an ideal run and an economical run as well. Many papers explored and investigated with a few novel initiatives indeed. In this paper, one of the most unique analyses has been discussed by considering rotational inertia and angular displacement of the wheel in the case of running on a battery only. On the other hand, based on the battery state of charge (SOC), battery ampere, as well as power splitting takes place between the battery and the internal combustion engine. The entire concept is described in this paper using a type 1 fuzzy logic controller (FLC) by incorporating Triplets as membership functions (MFs). In this work, the centre of area (COA) method is used for defuzzification. In this work, cascaded fuzzy is introduced as an Artificial Intelligence approach and applied in hybrid electric vehicles for intelligent optimum power splitting strategic planning. The study is theoretically constructed and validated using a few simulation-based results.

Fuzzy Sets and Systems
National Institute of Technology Durgapur (IN), Haldia Institute of Technology (IN)
Openalex Percentile: Top 52%
Geochemistry and Geologic Mapping
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Power Split Strategy Using Cascaded Fuzzy Control in a Hybrid Electric Vehicle · Fuzzy Sets and Systems (2024) | TGRS Research Map | TGRS