Lithium-ion batteries are playing important roles as energy storage solutions for portable devices, automotive electronics, and renewable energy systems. In order to maximize the performance of lithium-ion batteries, an advanced rapid-charging pattern is required. In this paper, a Taguchi-based algorithm is presented. Orthogonal arrays are implemented to determine the optimal rapid-charging pattern for multistage constant-current (CC)-charging method. Experimental results show that the obtained rapid-charging pattern is capable of charging lithium-ion batteries to 75% capacity in 40 min. The obtained pattern also provides 60% more cycle life than the conventional CC-constant-voltage method.

Search for an Optimal Rapid-Charging Pattern for Li-Ion Batteries Using the Taguchi Approach

In this study, a fast terminal sliding-mode control scheme is proposed as a new approach for the voltage tracking control of the DC-DC boost converter affected by disturbances, such as the variations in the input voltage and the load resistance. Some experiments are performed on a test bench to show the effectiveness of the proposed approach. The fast reference tracking capability with small overshoot and robustness to the disturbances of the designed controller is verified by the experimental results. Moreover, the results demonstrate that the proposed controller has a better performance related to conventional sliding mode and proportional-integral controllers in terms of the settling time and robustness to the disturbances.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-pel.2015.0008

Fast and robust voltage control of DC–DC boost converter by using fast terminal sliding mode controller

DC -
DC power supplies are playing significant role in different domains of engineering applications. Some converters such as boost, buck-boost, and fly-back have a right-half-plane zero (non-minimum phase system), hence it is difficult for the PID controller to exhibit good performance with load, line variations and parametric uncertainty. In this proposed work, design and implementation of type controllers have been performed by using k
-factor approach and two different optimisation techniques (gravitational search algorithm and particle swarm optimisation) for obtaining better stability and performance for a closed loop DC-DC Switched mode boost converter. The closed loop control system has been implemented in real time dSPACE platform. The comparative closed-loop performances of a boost converter with classical, optimised PID and optimised type II/type III controllers have been produced. Simulations and experimental results are provided to demonstrate the effectiveness of optimised controllers for the proposed converter. Design and implementation of optimised type controller for switch mode converters has not been reported earlier in any literature.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-pel.2015.0144

Design and implementation of type-II and type-III controller for DC–DC switched-mode boost converter by using K -factor approach and optimisation techniques

This paper presents an improved interleaved boost converter (IBC) with optimal Type-III controller by utilizing voltage mode control. Due to the presence of several power switches in parallel path, the degree of freedom has been increased in IBC. Also, the IBC produces lower output voltage ripples, so the size and losses of the output filter can significantly be reduced compared with conventional BC. But due to the nonminimum phase problem of IBC, closed-loop bandwidth is restricted that causes slower converter dynamics. It is difficult for the conventional proportional-integral-differential controller to exhibit good performance with line, load changes, and parametric uncertainty. So an optimal Type-III controller is designed and implemented for achieving better closed-loop dynamic performance and stability. Initially, controller parameters have been designed by using the classical “k-factor” method, and then particle swarm optimization-based optimal Type-III controller is developed for the proposed IBC. The comparative closed-loop performances of BC and IBC with classical and optimal Type-III controllers have been presented. The proposed control scheme by utilizing the optimized Type-III controller in IBC is newly introduced in this paper and has not been reported earlier. The overall control circuit diagram using voltage-mode controlled two-phase IBC has been implemented by simple analog control circuit and the cost of complete experimental setup is very cheap. Simulation and experimental results have been produced to show the efficacy of the proposed converter control system.

An Improved Interleaved Boost Converter With PSO-Based Optimal Type-III Controller

Buck DC–DC converter is used in many applications to supply a fixed amount of DC voltage. They are highly sensitive to the frequently changing loading conditions. Such a situation demands a robust control mechanism which can guarantee satisfactory performance of the buck converter over a widely changing load. This can be made possible by developing an adaptive control scheme which can estimate the true values of the uncertain load parameters in the least possible time. This paper proposes an adaptive Chebyshev neural network (CNN) based backstepping control technique for the output voltage regulation of a DC–DC buck converter. The proposed control strategy utilizes neural networks in approximating the unknown non-linear nature of load resistance by using orthogonal basis Chebyshev polynomials. CNN approximation tool in conjunction with the conventional backstepping procedure yields a robust control mechanism. The weights of neural network are tuned online using adaptive laws satisfying the overall closed loop stability criterion in the Lyapunov sense. The performance of the proposed control is demonstrated for wide range perturbations by subjecting the buck converter to changes in load resistance, input voltage and reference output voltage. Simulation studies are conducted to evaluate the performance of the proposed controller against radial basis function neural network based adaptive backstepping control and conventional adaptive backstepping. The results obtained are further verified from experimentation on a hardware setup using DSP based TM320F240 processor. Thus, the investigation confirms effectiveness of the proposed control scheme as the output voltage shows a fast and accurate response besides successfully rejecting the disturbances acting upon it.

An intelligent adaptive control of DC–DC buck converters

We propose a new method of controller design for a buck-boost type dc-dc converter in this paper. An optimisation model for the controller design is developed and solution is sought through a novel optimisation algorithm named as queen-bee assisted genetic algorithm (GA) which combines standard GA with evolution of queen bee in a hive. Computed and measured results suggest that the new algorithm converges to best designs on a limited number of iterations.

Buck-boost converter controller design using queen-bee assisted GA

This paper suggests a systematic design procedure for the feedback controller employed for the output voltage regulation of a buck type DC-DC converter using evolutionary algorithms, namely genetic algorithm, differential evolution and artificial immune system. Computer simulation results supported by experimental evidence clearly demonstrate that the controllers estimated through evolutionary algorithms are capable of delivering enhanced output voltage regulation under different types of load and supply disturbances.

Feedback controller design for a buck converter through evolutionary algorithms

The objective of this paper is to develop and analyze an analog circuit capable of delivering regulated output voltage in a dual input buck converter. The major components of the control circuit comprise a PI controller block and a duty ratio limit block. The PI controller is designed through linear control theory and the duty ratio limit on the each power switch is based on the relative amplitude of the source voltage connected to each power source. The development of the circuit is explained first followed by computed and measured results on a prototype.

A voltage constrained time sharing switching scheme for dual input buck converter

This paper suggests a systematic design procedure for the feedback controller employed for the output voltage regulation of a buck-boost type dc-dc converter using evolutionary algorithms namely Genetic Algorithm (GA), Differential Evolution (DE) and Artificial immune system (AIS). The output voltage regulation is formulated as an optimization task with the controller elements as the variables and solution is achieved through each evolutionary method. Computer simulation results supported by experimental evidence clearly demonstrate that the controllers estimated through evolutionary algorithms are capable of delivering enhanced output voltage regulation under different types of load and supply disturbances.

Feedback controller design for a buck-boost converter through evolutionary algorithms

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

S. Sankar

Author Tools

Chat about Author

Papers

Buck-boost converter controller design using queen-bee assisted GA

Feedback controller design for a buck converter through evolutionary algorithms

A voltage constrained time sharing switching scheme for dual input buck converter

Feedback controller design for a buck-boost converter through evolutionary algorithms