Performance Explorations of a PMS Motor Drive Using an ANN-Based MPPT Controller for Solar-Battery Powered Electric Vehicles

Teja, A. V. Ravi; Sultana, Razia; Salkuti, Surender Reddy

doi:10.3390/designs7030079

Cited by 12 publications

(3 citation statements)

References 42 publications

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“…The electric motor responds to the driver's demand, converts the energy from the battery energy storage system (ESS) to torque for propelling, and generates electricity to store in the battery ESS when the driver demands negative torque for braking. [34] The energy conversion efficiency can be described using the motor's efficiency map, which measures the energy conversion efficiency in percentage (Figure 2).…”

Section: Electric Motormentioning

confidence: 99%

Optimal Sizing, Gear Ratios, and Shifting Schedule of Battery‐Electric Mining Haul Trucks to Enhance Energy Efficiency

Liu,

Feng,

Liu

et al. 2024

Energy Tech

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At present, mining haul trucks (MHTs) directly deploy the on‐road heavy‐duty trucks’ battery‐electric powertrain, as they can cut down costs and emissions in mining. However, the operating patterns of MHT are different, e.g., ultraduty, low‐speed, and continuous road slopes, resulting in a mismatch between the dynamic and economic performance of mining required and the MHT achieved. The powertrain design and control influence the dynamic and economic performance, which can be quantitatively measured by top speed, gradeability, and energy consumption. This study uses an improved differential evolutionary algorithm to develop an integrated optimization platform to obtain the components sizing, gear ratio, and shifting schedule for the dedicated battery‐electric MHT. Mathematical models are established and validated using on‐site experiment data. An integrated optimization platform is initiated by concurrently formulating the motor sizing, gear ratio, and shifting schedule and solved by the improved differential evolutionary algorithm. Optimization results indicate that the economic performance is enhanced by 10.82%, 11.08%, 11.18%, and 11.20%, respectively, while maintaining or slightly improving the dynamic performance. Besides, the achievable maximum speed at the most common grade is boosted by 11.82%, 6.52%, 7.44%, and 6.52%, respectively. The study provides an approach to developing a battery‐electric powertrain for MHT.

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Section: Electric Motormentioning

confidence: 99%

Optimal Sizing, Gear Ratios, and Shifting Schedule of Battery‐Electric Mining Haul Trucks to Enhance Energy Efficiency

Liu,

Feng,

Liu

et al. 2024

Energy Tech

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“…A machine learning-based MPPT controller improves the PV array's effectiveness, ensuring ideal torque and steady speed for electric vehicles (EVs) under different load circumstances. The research employs a solar cell, SVPWM inverter, and DC-DC voltage booster to energize the EV, and the system's performance is assessed using MATLAB Simulink [27]. Microbe fuel cells (MFCs) transform organic substances into electric energy utilizing microorganisms, yet their limited power constrains their feasible use.…”

Section: Literature and Related Workmentioning

confidence: 99%

ANN-Based Reliability Enhancement of SMPS Aluminum Electrolytic Capacitors in Cold Environments

Jeong,

Kareem,

Song

et al. 2023

Energies

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Due to their substantial energy density and economical pricing, switching-mode power supplies (SMPSs) often utilize electrolytic capacitors. However, their ability to function at low temperatures is essential for dependable operation in several sectors, including telecommunications, automotive, and aerospace. This study includes an experimental evaluation of how well standard SMPS electrolytic capacitors operate at low temperatures. This paper investigates the suitability of standard electrolytic capacitors used in switched-mode power supplies (SMPSs) for low-temperature applications. The experimental evaluation exposed the capacitors to temperatures ranging from −5 °C to −40 °C, assessing capacitance (Cp), impedance (Z), dissipation factor (DF), and equivalent series resistance (ESR) at each temperature. The capacitor’s time-domain electrical signals were analyzed using the Pearson correlation coefficient to extract discriminative features. These features were input into an artificial neural network (ANN) for training and testing. The results indicated a significant impact of low temperatures on capacitor performance. Capacitance decreased with lower temperatures, while the ESR and leakage current increased, affecting stability and efficiency. Impedance was a valuable diagnostic tool for identifying potential capacitor failure, showing a 98.44% accuracy drop at −5 °C and 88.75% at the peak temperature, indicating proximity to the manufacturer’s specified limit. The study suggests further research and development to improve the performance of electrolytic capacitors in SMPS systems under cold conditions, aiming to boost efficiency and reliability.

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“…The development of electric vehicles (EVs) is intended to improve the use of renewable fuels while lowering pollution 1,2 . A future energy shortage has been predicted due to the depletion of fossil resources and an 80% increase in demand between 2020 and 2050.…”

Section: Introductionmentioning

confidence: 99%

A smart and intelligence based controlling algorithms for maximum power extraction and effective battery management in EV systems

Nambi,

Muthubalaji,

Srinivasan

et al. 2024

Energy Storage

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An economically appealing alternative to the use of fossil fuels in many nations is the electric vehicle (EV). Commercial EVs have a battery that powers the motor while also being charged by solar photovoltaic (PV). The original contribution of this research work is to implement a smart and advanced methodologies for accomplishing the objectives of MPPT control and battery management in EVs. Here, a novel spotted hyena optimized (SHO)‐MPPT controlling algorithm is applied to get the most out of the electricity generated by PV panels to meet EV energy requirements. A modified high gain super‐lift Luo converter has been implemented to improve and regulate the output voltage of PV for optimal battery charging and motor control. Then, an adaptive dynamic encoded network controller is designed to improve the voltage regulation and boosting performance of the DC‐DC converter. Consequently, a Henry gas solubility optimization is deployed to perform an effective battery management in EVs by optimally estimating the state of charge, which helps to increase the charging efficiency of EVs. Moreover, a three‐phase voltage source inverter has also been used to lower harmonic levels and deliver high‐quality output power to the EV motor. The results of the proposed MPPT controlling, converter controlling, and battery management strategies are verified in this study using a complete simulation and comparison analysis, where the parameters such as IV‐PV characteristics, motor torque, speed, total harmonic distortions (THDs), and so forth are taken into account for performance validation. By using the proposed controlling methodology, the THD is reduced to 1.09% with the improved vehicle speed of 3000 rpm, and overall performance efficiency of 99%.

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Performance Explorations of a PMS Motor Drive Using an ANN-Based MPPT Controller for Solar-Battery Powered Electric Vehicles

Cited by 12 publications

References 42 publications

Optimal Sizing, Gear Ratios, and Shifting Schedule of Battery‐Electric Mining Haul Trucks to Enhance Energy Efficiency

Optimal Sizing, Gear Ratios, and Shifting Schedule of Battery‐Electric Mining Haul Trucks to Enhance Energy Efficiency

ANN-Based Reliability Enhancement of SMPS Aluminum Electrolytic Capacitors in Cold Environments

A smart and intelligence based controlling algorithms for maximum power extraction and effective battery management in EV systems

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