This research work proposes a novel priority aware schedule based charging algorithm that uses wireless power transfer (WPT) technique in order to charge embedded sensor nodes (SNs) in a wireless body area network (WBAN). Implanted sensor nodes in WBANs require energy for both information extraction and data transmission to the remote controller unit. Thus, energy shortage of these SNs deteriorates due to the data transmission process of the patient health monitoring system. However, continuous operation by means of electromagnetic induction for energy harvesting, obtained from ambient sources, reduces the overall efficiency of the primary unit. With this paradigm in sight, an algorithm demonstrating the modeling of a priority-based mechanism is proposed in order to ensure proper sensor voltage level and to reduce the transmission losses. Medium access control (MAC) protocols are used for inductive powering from the primary unit to the secondary unit in a collision-free centralized scheduling scheme. Therefore, the proposed wireless charging algorithm for implanted SNs in WBAN is designed as per carrier sense multiple access with collision avoidance (CSMA/CA) technique. Because of this, the overall power consumption of SNs for certain operation periods, successful charging probabilities for multiple SNs, and instantaneous power requirements are considered as key performance measures of analysis. It is assumed that proper energy storage in both transmitters and receivers can handle channel interference and traffic contention. Simulation results verify that a significant reduction in power consumption for the proposed priority aware algorithm will maintain almost similar output. For this reason, saturating class-C as well as class-E driver circuits have been used to justify the performance in two different circuit topologies. Effects of priority with respect to the full charge period have also been observed for the multi-node system. Furthermore, from performance analysis, it has been demonstrated that the scheduling scheme causes both single MOSFET composed saturating class-C and Lchoke modeled class-E associated driver circuits to be considerably more loss efficient than corresponding existing ones.

A priority based energy harvesting scheme for charging embedded sensor nodes in wireless body area networks.

Cell balancing is a vital function of battery management system (BMS), which is implemented to extend the battery run time and service life. Various cell balancing techniques are being focused due to the growing requirements of larger and superior performance battery packs. The passive balancing approach is the most popular because of its low cost and easy implementation. As the balancing energy is dissipated as heat by the balancing resistors, an appropriate thermal scheme of the balancing system is necessary, to keep the BMS board temperature under a tolerable limit. In this paper, optimum selection of balancing resistor with respect to degree of cell imbalance, balancing time, C- rate, and temperature rise using machine learning (ML) based balancing control algorithm is proposed to improve the balancing time and optimal power loss management. Variable resistors are utilised in the passive balancing system, in order to optimize the power loss and to obtain optimal thermal characterization. The performance of the proposed system is evaluated using back propagation neural network (BPNN), radial basis neural network (RBNN), and long short term memory (LSTM). Error analysis of the balancing system is done to optimize balancing parameters and the proposed algorithms are compared using performance indices such as mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE) to validate the balancing model performance. The possible optimization scope for implementing passive balancing using machine learning algorithms are experimented in the Matlab-Simscape environment.

/pdf/machine-learning-based-optimal-cell-balancing-mechanism-for-3ejunv7awb.pdf

Machine Learning-Based Optimal Cell Balancing Mechanism for Electric Vehicle Battery Management System

Shipboard hybrid energy storage power system includes tens of thousands of single batteries. The performance of each single cell can't be completely consistent. Small differences will gradually increase after repeated charging and discharging, which may lead to a sharp decline of the performance and the cycle life of the battery. For imbalance performance between each single cell of shipboard hybrid energy storage, this paper proposes a multi-mode balance control method, which integrates fuzzy PID charging equalizer, sequential discharging equalizer and floating charging equalizer, in order to reduce the differences between the battery packs. According to the proposed balance control strategy, this paper takes an experiment on the battery packs for hybrid energy storage which are composed of lead-acid batteries, and achieves a better balance result.

The charging and discharging balance control strategy of power batteries for hybrid energy storage

This paper proposes a balancing strategy to improve the balancing performance of series-connected lithium-ion batteries The key point of the proposed strategy is to control the change rate of state of charge (SOC) of different batteries to be equal so that imbalance can be prevented from emerging and expanding With this strategy, the discrepancy of real maximum capacity in aged batteries can be mitigated and the lifespan of batteries can be prolonged In addition, the required balancing current of the equalizer is reduced owing to reduction of SOC gap, which helps minimize the energy loss during the balancing procedure The digital controlled Adjacent Cell to Cell (A-C2C) architecture is adopted, with which flexible and complex balancing strategies can be applied to the battery system A balancing experimental prototype with the aged batteries was built and verified the effectiveness of the proposed balancing strategy

Balancing strategy of lithium-ion batteries based on change rate of SOC

Electric Vehicle (EV)/Hybrid Electric Vehicle (HEV) enabled by high-efficiency electric motor and controller, provide the means for a clean, efficient and environmental friendly transportation system. Portable rechargeable batteries are the essential basic component in EVs. In EV/HEV system a large number of cells should be connected in series to supply enough energy, while the voltage balancing problem between cells leads to poor performance. This paper attempts modular battery charge equalization based on state of charge (SOC) under MATLAB Simulink environment.

https://iopscience.iop.org/article/10.1088/1757-899X/396/1/012052/pdf

Modular battery charge equalization circuit based on state of charge for electric vehicle application

The most basic requirement of all human life is energy. Nowadays the demand of energy consumption in India is becoming more. The need for power and energy develops in tandem with the population. In recent days/times the most used energy resource is renewable energy resources which can be utilised for various purposes. The most extensively used renewable energy source is solar energy. Solar energy is the most widely used renewable energy source since it is abundant, unlimited, pollution-free, and environmentally benign. This document displays a solar-powered irrigation pumping system. The solar irrigation pump system is one in which the functioning of a three-phase induction motor coupled pump system is powered by solar energy. The key variables influencing the amount of energy collected from a PV module is solar irradiation and ambient temperature. As a result, output energy will be generated in the PV array. One of the MPPT techniques used to track maximum power and enhance PV system efficiency is the incremental conductance method. MPPT generates the needed pulse based on the PV module’s output voltage. The DC-DC Converter, which is a boost converter, receives this pulse. The boost converter is used to regulate the voltage of the PV system. The boost converter utilised to provide the boosted DC output is the Dickson voltage multiplier. Three-phase VSI is used to convert DC electricity into high-frequency AC power. 

https://aip.scitation.org/doi/pdf/10.1063/5.0092263

Modeling and simulation of solar irrigation system with IM drive using PWM controller

Batteries are most widely used device to store the energy The importance of the batteries is increasing especially to store the energy harnessed from renewable energy resources The application of batteries in hybrid electric vehicles (HEV) is ever demanding and increasing The batteries when employed in stack, individual cell parameters will be altered due to the effects of temperature gradients, ageing effects and charging and discharging cycles Individual cells will have different SOC If the stack is considered as a two terminal device and allowed to charge, the individual cells in the stack will not be charged uniformly Few cells will be overcharged, few will be undercharged and few will be at the mid-range of its maximum value Continued use of stack with this condition will degrade the life of the batteries and the efficiency of the entire system drops to unacceptable range High-end battery users are aware of the uniformity to be achieved in the battery stack specially considering the valve regulated lead acid batteries The paper aims at having the equalization for series connected lead acid batteries The paper presents a simple and efficient active equalization scheme to equalize the batteries connected in series The implemented model checks the voltage value across each battery and identifies the battery with the weakest voltage The identified battery is allowed to charge without affecting the charging needs of other batteries in the stack The paper is to have a firsthand experience in equalizing the series connected batteries

Series battery equalization using sequential difference algorithm

This research work presents a non-conventional and effortless conversion of DC to AC voltage using a new method called Model Predictive Control which is also known as MPC with a LC Filter to reduce the harmonics in the waveforms for linear and non-linear loads using MATLAB Software. The Total Harmonic Distortion is very important in deciding the quality of the inverter output waveforms. The utilization of an Inverter with an output LC filter grants for the production of sinusoidal voltages with reduced harmonic distortion. The model predictive controller predicts the output voltages for all the feasible switching states produced by inverter. Then a cost function is utilized as a benchmark for choosing the switching state. The results show that the model predictive control method controls successfully the output voltage and performs very good when compared to conventional methods. The simulation results for balanced and unbalanced loads are performed using Matlab/Simulink tools, verifying the feasibility and good performance of the proposed control system.

Model Predictive Control Technique of Voltage Source Inverter for Linear and Non Linear Load

Battery Management System in Smart City: An Application of Cyber-Physical System

This project proposes a new power management system (PMS) charging station for hydrogen and electric cars that uses a diesel energy battery bank (BB), Diesel generator conversion system (DECS), and photovoltaic (PV) with hydrogen unit (HYG) and fuel cell unit (FC). The control goals of the proposed PMS system are to guarantee battery management based on PV irradiance, Diesel generating capacity, Hydrogen level, and Fuel cell capacity, (ii) to reduce system power loss (high efficient), and (iii) to improve system dependability and power quality. The power management and stability of an Electrical Vehicle-connected system with a large-scale Diesel generator (DG)-photovoltaic (PV) and Fuel cell (FC) with hydrogen unit, as well as an energy-storage unit based on battery, are suggested in this project. This project is developing an off-grid charging infrastructure for hydrogen and electric cars. It is feasible to charge both hydrogen and electric cars at the same time. They show as two hydrogen and electrical load demands at the charging station. The charging station is powered by solar panels. A bidirectional buck boost converter is utilized as an extra converter unit for the battery, hydrogen, and fuel cell units. The suggested PMS approach exhibits superior operational performance in terms of grid reliability improvement, loss reduction, load sharing, and battery management under operating circumstances. Simulating the suggested system is done in the MATLAB/SIMULINK environment. 

B S Sagar

Papers

Modeling and simulation of solar irrigation system with IM drive using PWM controller

Series battery equalization using sequential difference algorithm

Model Predictive Control Technique of Voltage Source Inverter for Linear and Non Linear Load

Battery Management System in Smart City: An Application of Cyber-Physical System

Energy management system for charging stations for electric and hydrogen vehicles using solar, hydrogen and fuel cell technology