A Heuristic Algorithm for Determining State of Charge of a Lead Acid Battery for Small Engine Applications

Aim: The study examined the effect of time on amount of voltage generated in a foot beat electricity generating system stored in a battery.
 Study Design: A system made of piezoelectric materials was designed such that the foot beats of dancers on a platform would cause a mechanical deformation that would lead to conversion of mechanical energy due to pressure from the foot beats to electrical energy; and can be stored in a rechargeable lead acid battery for future use.
 Place and Duration of Study: Awka Anambra State, Nigeria, between November 2018 and April 2020.
 Methodology: A sheet of plywood measuring 300 mm x 300 mm x 3 mm thick was placed on a hard wooden board of 300 mm x 300 mm x 25 mm thick where twelve piezoelectric sensors were connected in series with foam spring inserted as separators and to aid in returning after deformation. As the dancers step on the platform, multimeter was used to take the voltage and current readings, while Lead acid rechargeable battery could be connected at the output point to store energy generated in the system and or Light Emitting Diodes (LED) and Universal Serial Bus (USB) outputs. A stop clock was also used to take the time.
 Results: The study revealed that it would require 901 seconds for a 50kg dancer to increase a unit voltage state of charge in a battery. It also found that it would require 749 seconds for a 60 kg dancer; and 595 seconds for an 80kg dancer respectively to increase the same 1-unit voltage state of charge in a battery. The study showed that the voltage in the battery would continue to increase until the battery is fully charged at which point it is expected that there would no longer be any increase in charge in the battery irrespective of increase in the number of foot beats or time.
 Conclusion: The result implies that the charge in battery caused by pressure from the foot beats is subject to the maximum voltage capacity of the battery in the system. Likewise, the amount of time and number of foot beats required to add a unit voltage state of charge in a battery in the system is subject to the applied pressure from the foot beats. In view of this, the study craves for popularisation of this technology through large scale research supported by government, corporate organisations or international organisations and institutions that will support new products development in the building and construction industry as it is the case in India and other developed countries.

A realistic model for battery state of charge prediction in energy management simulation tools

Solar photovoltaic charging of lithium-ion batteries

The charging of Lead-acid battery with pulses has other advantages besides the desulfation phenomenon on electrodes. The quantity of energy that is invested into charging the battery with pulses doesn't have an homogenous graph with regards to the variation of duty cycle. The experimental measurements of quantities of energy for charging of battery show the existence of maxims and minims on the frequency domain between 33 Hz – 100 kHz with various duty cycle. This fact is caused by the physical and electrochemical properties of particles, which determine the speed of motion and reaction under electrical field.

State of charge estimation of lead acid batteries is critical for applications that rely on backup power like UPS sytems for telcom operators, data centers, renewable energy installations. Estimating the state of charge of a lead acid battery is a tough job mainly because there is no clear way to predict the behavior of the batteries. One of the common methods of estimation of state of charge of a lead acid battery is by means of measuring the terminal voltage of a lead acid battery. This is not very accurate, but due to its ease of use, it is widely adopted. The current reasearch into estimating the state of charge of a battery is by means of using intelligent control techniques. This paper proposes a methodology by using neural networks. By relying on the parameters of terminal voltage of the battery, load current, temperature of the battery, specific gravity of the electrolyte a methodology is proposed. An Adaptive Neuro Fuzzy Inference System is used here. This system improves the accuracy of the existing methods by using specific gravity when the battery is discharging. The developed topology was tested by using sample data obtained from a manufacturer's datasheet and the benifits of multiparameterized approach was vidicated.

Influence of the charge regulator strategy on state of charge and lifetime of VRLA battery in household photovoltaic systems

Objective: Good knowledge of safety measures against hazards of lead-acid battery work is important in the control of the work-related health problems. The study assessed the effects of training on knowledge, attitude and practice of safety measures among battery chargers in Ilorin, Nigeria.Methods: The study was a quasi-experimental (non-randomized) study with pretest and post-test design. A total of 107 battery chargers were recruited each for intervention and control group. The study group was offered training on occupational safety measures while the control group did not have training at this stage. Post intervention data was collected 12 weeks after the pre-intervention. Multistage sampling technique was used to select 214 registered battery chargers working in Ilorin in to the study. Data obtained through interviewer-administered questionnaires were analysed using SPSS version 16 software.Results: Less than one-fifth (15.9%) of the study group had good knowledge of hazards relating to battery which increased significantly to more than three-quarters (76.2%) post-intervention. The majority (85.0%) of the study group and (86.0%) of the control group had positive attitude towards safety measures pre-intervention. There was no significant improvement in attitude post intervention. The safety practice of less than one-tenth (6.5%) of the study group was rated good pre-intervention which increased significantly to almost one-fifth (17.8%) post-intervention. There was no significant improvement in the Kwowledge, attidude or practice of safety measures among the control group post intervention.Conclusion: Association of the battery chargers should organize in conjunction with the health institutions training of their members on hazards prevention and safety practices.Keywords: Training, battery, safety measures, workers, Ilorin

For saving energy, lead acid battery plays an important role in photovoltaic system. Battery state of charge estimation is a key function of battery management system due to the requirement of ensuring optimum operation and safety. Therefore, for achieving a fiable operation, it is necessary to develop an accurate model for the estimation of the state of charge (SOC) of battery. In this paper, a RC equivalent circuit model has been presented. A state representation of battery has been developed. A kalman filter has been proposed to determine the SOC. The model of battery and the recursive algorithm have been implemented on Matlab-Simulink and Simpower softwares. Recovered simulation results have been compared by an experimental works applied to a lead acid battery 12V, 7Ah. Obtained results show an acceptable correspondence with the experimental test. The kalman filter approach can be an useful tool for researchers to imitate the real behaviour of the battery and to ensure the accurate estimation of SOC.

Optimal charging of stand-alone lead-acid and lithium-ion batteries is studied in this paper. The objective is to maximize the charging efficiency. In the lithium-ion case two scenarios are studied. First only electronic resistance is considered and in the next step the effect of polarization resistance is also included. By considering constant model parameters for the lithium-ion battery analytical solutions exists for both scenarios using Pontryagins minimum principle. In lead-acid chemistry the variation of total internal resistance with state of charge (SOC) is considerable and the optimal charging problem results in a set of two nonlinear differential equations with one initial and a final condition to be satisfied. This so called two point boundary value problem is solved numerically.

Elman neural network using ant colony optimization algorithm for estimating of state of charge of lithium-ion battery

In smart grid environment, batteries charged from grids during off peak hours (specially late night) for use either in electric vehicles or as emergency power source play an important role as Distributed Energy Resources (DERs) at the demand side. It is important to estimate the support available from such a resource for energy management during a contingency. In this paper, a dynamic (time varying) model of charging with constant current has been developed for lead acid batteries. This model provides a means to compute analytically the open circuit voltage (OCV) at a given time and the corresponding state of charge (SOC). A few sets of data obtained from practical tests of different sizes of batteries have been used to determine model parameters. The model is then applied to another battery and the output compared with its available test data for validation. As lead acid batteries are very common and affordable these have been used in this work. However, the methodology reported in this paper can always be extended to develop similar models for Nickel Metal Hydride (NiMH) or Lithium ion (Li-ion) batteries. Therefore, this paper presents a generic model that can be used for other, newer battery types.

In order to fully cover the V-I plane of deep-cycle batteries, battery chargers should work under different loading conditions and output voltage, and should respond to different States of Charge (SoC). In this paper, a fourth order L3C resonant converter is introduced and employed as a battery charger. The analytical equation of the L3C voltage gain shows the possibility of regulating wide output voltage to an unprecedented degree within a narrow frequency range to cover the entire V-I charging plane of modern batteries. The topology integrates all of the parasitics elements into the resonant circuit, realizes ZVS for the inverter MOSFETs, and provides inherent over-current protection capacity. These advantages provided by the proposed L3C resonant converter make this topology an excellent candidate for use as a charger in Electric Vehicles. The experimental results extracted from a 220V DC; 550W resonant converter platform with a peak efficiency of 96:5% exhibit the excellent performance of the proposed converter for battery charger applications.

Battery chargers come in different shapes, sizes and capacities, but it is difficult (if not rare) to find one charger unit that regulates overcharge and can charge different battery voltages. This work uses the basic electrical principles and ICs, to design a user friendly charger circuit that manually adjusts the voltage depending on the voltage of the battery, (6volts, 9volts and 12volts was considered because it is generally available). The circuit charges in three modes namely: Burst charging, trickle charging and pulse charging. It also incorporates a Liquid Crystal Display (LCD) to display the voltage that is being charged. The circuit also uses a Pulse Width Modulator (PWM) in order to control the duty cycle and voltage. The circuit also has an overcharge and over discharge protection. This remarkable charger saves the user time and resources needed to purchase three different chargers for three batteries, with different voltages. From the result obtained the built battery charger was able to charge 6volts (10Ah), 9volts (1200mAh) and 12volts (10Ah) battery to 100% state of charge. The charging time for the 6volts battery was 2hours 24 minutes, 2 hours 36 minutes for the 9volts battery and 2 hours 30 minutes for the 12volts battery.Keywords: Burst Charge, Depth-Of-Discharge DOD, Pulse Charge, State-Of-Charge SOC, Trickle charge, Duty Cycle

현재 전기자동차와 신재생에너지전원의 출력안정화에 필수적인 2차전지가 개발되고 있고, 2차전지의 효율적인 운용을 위하여 상태감시 기술과 수명예측 기술이 요구되고 있다. 기존의 2차전지 상태감시 방법으로는 전압과 비중에 의한 충전상태평가 방법 등이 있으나, 이 방법은 온도에 따라 변화되는 전압과 비중의 특성을 고려할 수 없는 한계점을 가지고 있다. 즉, 2차전지의 SOC를 평가하기 위해서는 전지 케이스 내부의 전해액 온도에 따라 달라지는 비중 값을 측정해야 하지만, 대부분의 2차전지는 밀폐형으로 보급되고 있어서 전해액의 상태를 파악하기 어려운 실정이다. 따라서 본 논문에서는 전지내부의 온도를 보정하는 열전달식을 유도함으로 정확한 SOC평가 알고리즘을 제시하였다. 또한 2차전지의 수명 예측 방법으로는 내부저항 측정 또는 잔존 용량 측정 등의 수명 예측 방법들이 있으나, 충 방전상태와 충전 후 방치시간, 사용 환경 등 여러 가지 요인에 의해 2차전지의 수명을 정확하게 판단하기 어렵다. 따라서 상기의 문제점을 해결하기 위해 <TEX>$20^{\circ}C$</TEX>로 환산된 비중 값에 대하여 전지의 충 방전에 대한 비중누적 값을 계산함으로 충 방전 사이클을 판정하는 수명예측 알고리즘을 제시하였다. 상기에서 제시한 알고리즘을 바탕으로 시험 장치를 제작하여 다양한 시뮬레이션을 수행한 결과, 기존의 방법에 비하여 본 논문에서 제안한 알고리즘이 정확한 연축전지의 상태감시 및 수명예측에 대한 결과를 얻을 수 있음을 확인하였다. This paper deals with the state of charge(SOC) and life cycle evaluation algorithm for lead-acid battery, which is essential factor of the electric vehicle(EV) and the stabilization of renewable energy in the smart grid. In order to perform the effective operation of the lead-acid battery, SOC and life cycle evaluation algorithm is required. Specific gravity with the change of electrolyte temperature inside battery case should be obtained to evaluate the SOC of lead-acid battery, however it is difficult to measure the electrolyte temperature of sealed type lead-acid battery. To overcome this problem, this paper proposes the equation of thermal transmission to compensate internal temperature of the lead-acid battery. Also, it is difficult to exactly evaluate the life cycle of battery, depending on the operation conditions of lead-acid battery such as charging and discharging state, self discharging rate and environmental issue. In order to solve the problem, this paper presents the concept for gravity accumulation of charge and discharge cycle, which is the value converted at <TEX>$20^{\circ}C$</TEX>. By using the proposed algorithm, this paper propose the test device based on the Labview software. The simulation results show that it is a practical tool for the maintenance of lead-acid battery in the field of industry.

For the purpose of predicting the state of charge of Lithium-ion rechargeable battery accurately, we introduced the method of electrochemical impedance spectroscopy to solve the problem. The experiment data of impedance spectroscopy is comprised of an inductive arc in the high-frequency region and two capacitive arcs in the low-frequency region, and by which the reasonable equivalent circuit of battery was established. The component parameters obtained at several state of charge values of the battery had been analyzed by a non-linear least-squares fitting procedure and some electrochemical knowledge. Through researching the changing regulation of parameters with the different States of charge, the frequency of maximum of the semicircle (f max ), the phase angle o, the equivalent series capacitance (C s ) had been substantiated to be the suitable parameters for analyzing and predicting the state of charge values of the lithium-ion battery.