Multivariate optimization for maximum capacity of lead acid battery through Taguchi method

Vyas, Mayank; Jain, Mahaveer K.; Pareek, Kapil; Garg, Akhil

doi:10.1016/j.measurement.2019.106904

Cited by 12 publications

(11 citation statements)

References 24 publications

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“…Taguchi proposed a quality-enhancement methodology, popularly known as the Taguchi method. 29 Taguchi method has been extensively used for optimization problems with a clearly stated objective function whose aim is to determine the optimal parameter setting for a process while comprehensively reducing the necessary number of experiments without compromising the integrity of the process. 30 The analysis conducted upon the results of experiments carried out using Taguchi design focuses on achieving one of the following objectives…”

Section: Methodsmentioning

confidence: 99%

Study on the optimum orientation of bifacial photovoltaic module

Raina

Raghunathan

Sinha

2021

Intl J of Energy Research

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The idiosyncrasy of bifacial photovoltaic devices by means of its ambivalent nature in absorbing irradiation demarcates this technology from conventional monofacial modules. The performance of bifacial PV devices is primarily a function of the orientation of the device, that is, its tilt angle (β), the elevation of the module above the ground (E), the albedo of the location (ρ g ) and the azimuth angle (γ). The current work, focusing on determining the optimum setting for module installation, takes into consideration three factors, namely, β , E(m) and γ , concentrated on maximizing the power generation from the test bifacial PV module at Jaipur, India (26.91 N, 75.78 E) using full factorial design experiment through Taguchi method. Based on Taguchi analysis, the optimal parameter setting for maximizing response obtained is β = 40 , E = 0.8 m and γ = 22.5 . Adequacy of the design was determined through ANOVA, which presented a high R 2 value of 88.7%. The results for optimal parameter setting obtained using Taguchi design are validated through experiment, and the error in computed value and experimentally determined value of response is 2.64%. The PR of the module installed at optimum orientation, upon investigation, was highest among test orientations (84.76%) due to greater rear side irradiance collection. Further results show that increasing albedo increases the output for modules installed at optimum orientation. The results are also verified against empirical relations presented in the literature to highlight the competency of the results.

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Section: Methodsmentioning

confidence: 99%

Study on the optimum orientation of bifacial photovoltaic module

Raina

Raghunathan

Sinha

2021

Intl J of Energy Research

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“…As a result, lead sulfate cannot be quickly convertes to lead and accumulates on the surface and inside the negative plate, resulting in a greatly reduces capacity of the negative plate. 49,50…”

Section: Resultsmentioning

confidence: 99%

Increasing the oxygen-containing functional groups of oxidized multi-walled carbon nanotubes to improve high-rate-partial-state-of-charge performance

Peng

Gao

et al. 2022

RSC Adv.

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“…Figure 3 shows the schematic layout of the test workbench setup for battery dataset development. Instrumentation for dataset development includes battery test platform that comprise of an advanced programmable battery tester, CADEX C8000 and programmable environmental chamber 41,42 …”

Section: Methodology and Experimentationmentioning

confidence: 99%

“…A programmable electronic DC load was used to provide current measurements with an accuracy of ± (0.1% Full Scale Deviation [FSD]) at 1 mA resolution. All data measurements are taken at the sample rate of 5 seconds 42 …”

Section: Methodology and Experimentationmentioning

confidence: 99%

State‐of‐charge prediction of lithium ion battery through multivariate adaptive recursive spline and principal component analysis

et al. 2020

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The main aim of this research work is to provide a comprehensible state of art for the intensification of the utmost decisive task performed by a modern BMS system to monitor and estimate battery states through a well‐entrenched statistical analysis method. In the present work, “multivariate adaptive regression splines” (MARS) method along with principal component analysis (PCA) has been used to develop a predictive model‐based state of charge (SoC) estimator for an NCR 18650PF Lithium ion battery at constant charging c‐rate of 0.3 C and 0.3 C and 0.5 C constant discharge profiles. Time‐weighing factors, that is, voltage‐current and temperature are employed as training datasets, to provide greater impact for developing a SoC MARS model of with high coefficient of correlation R2 (0.9984). The SoC MARS model adequacy is then validated for voltage prediction of the same battery for two different profiles of discharging using NIPALS algorithm for principal component analysis (PCA) with SS2 of 93.69% and 94.23% for profile A and profile B, respectively.

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Multivariate optimization for maximum capacity of lead acid battery through Taguchi method

Cited by 12 publications

References 24 publications

Study on the optimum orientation of bifacial photovoltaic module

Study on the optimum orientation of bifacial photovoltaic module

Increasing the oxygen-containing functional groups of oxidized multi-walled carbon nanotubes to improve high-rate-partial-state-of-charge performance

State‐of‐charge prediction of lithium ion battery through multivariate adaptive recursive spline and principal component analysis

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