Fuzzy logic-based voltage regulation of hybrid energy storage system in hybrid electric vehicles

Hussan, Umair; Majeed, Muhammad Asghar; Asghar, Furqan; Waleed, Aashir; Khan, Asim Ali; Javed, Muhammad Rameez

doi:10.1007/s00202-021-01315-4

Cited by 20 publications

(10 citation statements)

References 29 publications

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“…However, they often do not operate effectively at variable speeds; also, complex mathematical models and nonlinear behavior create difficulties in variable speed operations. 7,22,23 The particle swarm optimization (PSO) algorithm of the PID controller was introduced to interleave the buckboost power converter (BBPC). However, the peak overshoot was not minimized by the PSO algorithm.…”

Section: Motivation and Research Gapmentioning

confidence: 99%

“…Therefore, the development of a speed controller that eliminates external disturbances and sustains road uncertainty with reduced control action has become a key issue to be addressed. [5][6][7][8][9][10] DC-DC converter is an important component for an EV. Under normal conditions, the vehicle maintains its stability.…”

Section: Introductionmentioning

confidence: 99%

“…However, due to changing road dimensions, load parameters, and external disturbances, the control system is nonlinear, timedependent, and unpredictable. Therefore, the development of a speed controller that eliminates external disturbances and sustains road uncertainty with reduced control action has become a key issue to be addressed 5–10 . DC‐DC converter is an important component for an EV.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the research work has more attention in the design of fuzzy logic controllers (FLCs) because of its robustness, flexibility, computational elements, control blocks, and discrete control‐driven systems. However, they often do not operate effectively at variable speeds; also, complex mathematical models and nonlinear behavior create difficulties in variable speed operations 7,22,23 . The particle swarm optimization (PSO) algorithm of the PID controller was introduced to interleave the buck‐boost power converter (BBPC).…”

Section: Introductionmentioning

confidence: 99%

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A novel cat swarm optimization‐based fuzzy PI controller for improving dynamic response of converter

Priya,

Balakumaran

2023

Asia-Pacific J Chem Eng

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Nowadays, the use of fuel cells in various applications has become very widespread. Some of their most important applications are in electric vehicles (EVs) and local off‐grid power systems. An EV works as an electric motor that burns a mixture of fuel and gases to generate electricity. One of the challenges with fuel cells is the slow dynamic response to load power changes. In the past few decades, the modeling and control of DC‐DC converters have undergone extensive research and development. However, the error, settling time, and peak overshoot performance are not reduced by the robust nonlinear controller and current mode controller. To overcome these problems, quantile regressive extreme seeking cat swarm optimized Mamdani fuzzy PI controller (QRESCSO‐MFPIC) approach is developed. The goal of the QRESCSO‐MFPIC approach is to reduce the integral time absolute error (ITAE) for tuning the fuzzy PI controller. Initializing the fuzzy PI controller parameter is an input in the QRESCSO‐MFPIC approach. For every parameter value, the fitness function is determined and quantile regression analysis is carried out. The efficiency of the QRESCSO‐MFPIC approach is measured by evaluating the settling time and peak overshoot. Tuning of the PI controller is carried out with cat swarm optimization (CSO) and particle swarm optimization (PSO) based on the objective function of ITAE. The result analysis shows that the QRESCSO‐MFPIC approach improves the efficiency of an optimized Fuzzy PI controller compared to the existing methods. Peak overshoot reduction and settling time are improved through the QRESCSO‐MFPIC approach than the proportional integral particle swarm optimization controller (PI‐PSO).

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Section: Motivation and Research Gapmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A novel cat swarm optimization‐based fuzzy PI controller for improving dynamic response of converter

Priya,

Balakumaran

2023

Asia-Pacific J Chem Eng

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“…Although FLC produces excellent results, it may not always indicate the best answer in certain scenarios. In [118,119], the authors implemented the FLC controller for battery charging applications. e results showed that the converter produced good results when compared with other controllers.…”

Section: Fuzzy Logic Controlmentioning

confidence: 99%

An Extensive Critique on Electric Vehicle Components and Charging Systems

Iqubal

Sathiyan

Stonier³

et al. 2022

International Transactions on Electrical Energy Systems

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Nowadays the demand for electric vehicles has been increasing due to their dropping price range and zero emission of carbon. This article initially discusses the development of various electric vehicles from the past to the present. Since the electric motor plays a significant role in EVs, various motors suitable for EVs have been identified and surveyed in this work. The battery storage system is a critical component of EVs; hence, the article goes over all the different types of batteries, from lead acid to lithium ion. Additionally, the other vehicle components such as converters required for charging the batteries, intelligent controllers, electric vehicle charging process, power management, and battery energy management concepts that are available are discussed in detail. Moreover, we bring our work to a conclusion by outlining the research opportunities that remain for the academic and industrial groups. Therefore, the proposed work intends to assist as a state-of-the-art reference for researchers in the field of various electric vehicle configurations, storage systems, converter configurations, charging techniques, control methods, and modulation methods.

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Fast dynamic control for a boost DC/DC converter in hybrid-electric powertrain with PEM fuel cell and battery pack

et al. 2023

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When working with hybrid-electric powertrain with a proton exchange membrane fuel cell (PEMFC) along with a battery pack, to increase the life of the PEMFC and avoid a drop of performance it needs to be periodically short circuited. The periodic short circuit of the PEMFC requires the DC/DC converter to be decoupled from the PEMFC. This behaviour leads the converter to undergo several start-up transients, and for an optimal energy management, the converter must reach its reference steady-state condition as quickly as possible. In this frame, this paper presents an innovative dynamic control for current mode operations of a boost DC/DC converter for managing the power exchange between the fuel cell and the battery pack, which could be easily implemented in industrial applications. With the proposed control system, the converter achieves faster step response when turned on, reducing the time required by the controlled current to reach its set point. To support theoretical considerations and simulations results, an experimental validation has been performed with a real system prototype.

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Fuzzy logic-based voltage regulation of hybrid energy storage system in hybrid electric vehicles

Cited by 20 publications

References 29 publications

A novel cat swarm optimization‐based fuzzy PI controller for improving dynamic response of converter

A novel cat swarm optimization‐based fuzzy PI controller for improving dynamic response of converter

An Extensive Critique on Electric Vehicle Components and Charging Systems

Fast dynamic control for a boost DC/DC converter in hybrid-electric powertrain with PEM fuel cell and battery pack

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