Battery Terminals Research Articles

Data driven approach for state-of-charge estimation of lithium-ion cell using stochastic variational Gaussian process

Modern electric vehicles rely on lithium-ion batteries. Electric vehicles (EVs) utilize intricate battery packs that require the oversight of a battery management system (BMS) to ensure safe, reliable, and efficient operation. The state estimation of the battery pack is an important responsibility carried out by the BMS. Accurately estimating the State-of-Charge (SOC) poses a considerable engineering challenge since it cannot be directly measured at the battery terminals. This study introduces a novel data-driven methodology for accurately estimating the SOC in Lithium-ion batteries, with a particular focus on its relevance in EV contexts. The framework is built upon the Stochastic Variational Gaussian Process (SVGP)—an improved version of the conventional Gaussian Process (GP). Unlike GP, It can scale up to very large datasets. Furthermore, SVGP uses variational inference to estimate the posterior instead of calculating, making it computationally efficient. The model training process involves using laboratory test data from an 18650 Lithium-ion Nickel Manganese Cobalt (NMC) cell that has gone through eight dynamic drive cycles. The findings showcase a remarkable level of precision in estimation, as indicated by an average R2 value of 0.99 and a Mean Square Error (MSE) as low as 0.02.

Assessment of Maintenance Activities and Strategies for Tractor and Operator Care in Gurage Zone, Wolkite Town, Ethiopia

Data was collected from 53 tractor operators and stakeholders from the Wolkite. Many types of tractors were used and the common brands were Sonalika, Indo-farm, John Deer, Massey, Fergusson, and New Holland. Of these tractors, about 30.18%, 20.75%, and 18.86% were used for plowing, harrowing, transporting, threshing, planting, and spraying activities by Sonalika, Indo-farm, and John deer respectively. Regarding training to operate the machine, about 71.69% replied yes and about 28.31% replied don't have the training to maintain the machine, but they develop their skills through different experiences. But for their maintenance activities, they replied as 22.64% for daily, 92.45% for weekly, and 100% for monthly. In the case of checking the fluid level of the tractors about 9.43% within 3 hours, 20.75% within 6 hours, and 84.9% within 10 hours with oil level, about 3.77% within 3 hours, 11.32% within 6 hours and 98.11 within 10 hours for checking the water level and lastly about 15.09% within 3 hours, 71.69% within 6 hours and 94.33% within 10 hours to check the level of fuels. Moreover the washing of the tractors after the operation was 1.88% washed their tractors after operation; about 5.66% didn't wash their tractors, and about 92.46 washed without schedule. For lubricating different rotating parts of the tractors, about 56% of the respondents lubricate their tractor parts and about 92.45% of the respondents clean the battery cables and terminals frequently. About 3.77% and 16.98% use shelter for their tractors and record-keeping experience during their work.

FPGA-Based VFF-RLS Algorithm for Battery Insulation Detection in Electric Vehicles

As the adoption of electric vehicles (EVs) continues to rise, attention has switched to ensuring the safety of EV operations. The exponential growth in battery technology over the past several years has changed the face of energy storage and sparked a revolution in several industries. The degradation of battery insulation during regular use is a significant concern. The high voltage (HV) and current levels in HV electric vehicles pose a significant electrical threat.The advancement of electric vehicle technology has led to an increasing presence of HV electric equipment throughout the vehicle. The insulation strength and early health status detection of the batteries are essential in ensuring safety in EVs. This paper studies the different insulation detection techniques and the development of adaptive filter (AF) algorithms based on field-programmable gate arrays (FPGAs) for insulation detection. FPGAs are amongst the most accurate and fast detection techniques among all the insulation detection techniques used so far in electric vehicles. This study proposes an FPGA-based VFF-RLS algorithm for effectively implementing insulation detection in EVs. The experimental test results using FPGAs demonstrate that the proposed method can rapidly monitor changes in insulation resistance (IR). The VFFRLS-based FPGA technique works sufficiently well to reduce errors when dealing with variations in voltage and resistance conditions at the battery terminals.

A Hybrid Energy Storage System Integrated with a Wave Energy Converter: Data-Driven Stochastic Power Management for Output Power Smoothing

Beyond solar and wind energy, wave energy is gaining great interest due to its very high theoretical potential, although its stochastic nature causes intermittent and fluctuating power production. Energy storage system (ESS) integration to wave energy converter (WEC) plants represents a promising solution to mitigate this issue. To overcome the technological limits of the single storage devices, the hybridization of complementary ESSs represents an effective solution, extending the operating range over different timeframes. This paper analyzes the benefits of Li-ion battery–supercapacitor hybrid ESS integration into a grid-connected WEC, aiming at smoothing the produced power oscillations. The hybridization concept involves coupling a power-intensive technology, such as a supercapacitor devoted to managing fluctuations at higher frequency, with a battery technology exploited to manage power variations over longer timeframes to mitigate degradation issues. In this study, a multi-objective data-driven power management strategy, based on the simultaneous perturbation stochastic approximation (SPSA) algorithm, is implemented to minimize power fluctuations in terms of power ramp (representing the power variation between two consecutive values with a 1 s time step), both at the Point of Common Coupling (PCC) and the Li-ion battery terminals, thanks to the supercapacitor peak-shaving function. The SPSA management strategy, together with a suitable sizing procedure, allows a reduction of more than 70% in the power oscillations at the PCC with respect to those at the WEC terminals, while decreasing battery stress by more than 25% if compared to a non-hybrid ESS consisting of a Li-ion battery. This shows how supercapacitor features can extend battery lifespan when integrated in a hybrid ESS.

Working Temperature’s Influence on the Lifepo4 Battery Generated Power

Abstract The battery needed to store electricity is an essential element of a photovoltaic energy production system. The place where this system element is located, during its operation, will thermally influence the way the battery works. The specialized literature presents studies on the influence of temperature on the electrical working capacity of the battery, but through this scientific paper we want to study a concrete case of a LiFePO4 battery and quantify the influence of temperature differences in the working space on the differences in the energy capacities generated by the same battery. The experimental setup allowed recording the temperature of the space where the battery is placed for a long time, so we ensured that the temperature of the battery is approximately equal to that of the working space, just like in a real case of a photovoltaic system. The monitoring of the electric power of the battery in operation was carried out only during its discharge, by imposing a constant discharge current simultaneously with the recording of the voltage at the battery terminals throughout this cycle. At the end of the experiments, we associated the average temperatures during the discharge cycles with the average powers discharged by the battery in each thermal frame. The quantification was achieved by relating the power differences generated to the temperature differences of the different thermal situations experienced. The importance of this study resides into the highlighting of importance to maintain an optimal temperature for the space where the batteries are stored, having as technical effect the maintaining the power’s functioning optimal rate of these. The design of a photovoltaic system must be oriented to a long term calculus regarding power’s rate depending by battery’s working space temperature.

Nonlinear control design and stability analysis of hybrid grid-connected photovoltaic-Battery energy storage system with ANN-MPPT method

The problem of controlling a grid-connected solar energy conversion system with battery energy storage is addressed in this work. The study’s target consists of a series and parallel combination of solar panel, DC/DC converter boost, DC/AC inverter, DC/DC converter buck-boost, Li-ion battery, and DC load. The main objectives of this work are: (i) PV voltage regulation: the PV panel voltage must track a given reference voltage corresponding to the maximum power point. The optimal reference voltage is generated by an optimizer based on the artificial neural network (ANN); (ii) DC link voltage regulation: The DC link voltage must track a reference voltage as closely as possible. (iii) PFC requirement: The grid currents must be sinusoidal with the same frequency and in phase with the voltage grid. The periodic nature of solar energy and the frequent fluctuations in load demand reduce battery life and charging performance. To deal with these limitations and ensure the battery’s safety, a battery energy management algorithm is developed with the following objectives: (iv) CC mode: When the battery’s state of charge is less than 100% (SOC<100%), it indicates that the battery is not fully charged, this aim has been adopted. The battery current should follow a constant reference as closely as possible to the permissible limits battery current; (v) CV mode: When the battery is completely charged, this mode is switched on. The voltage at the battery terminals then achieves its reference signal, which corresponds to the charge state’s of the battery SOC=100%. In addition, the energy management system which generates several energy flow scenarios, in this work, the focus is to balance the energy flows between the load and the different energy sources to minimize the system costs, to ensure the stability of the grid and to improve the power quality. To do this, a mathematical modeling of the overall system was performed. Subsequently, backstepping controllers are then synthesized in order to ensure the control objectives. The closed loop control convergence is formally analyzed using Lyapunov’s stability theory and its performances are illustrated by simulation. As a result, the simulation results indicate that the proposed controllers perform admirably in achieving their objectives.

Discharging of Spent Cylindrical Lithium-Ion Batteries in Sodium Hydroxide and Sodium Chloride for a Safe Recycling Process

Battery discharging prior to size reduction is an essential treatment in spent lithium-ion battery recycling to avoid the risk of fire and explosion. The main challenge for discharging the residual charges by immersion in an electrolyte solution is corrosion because of electrolysis reactions occurring at the battery terminals. This study investigated the discharging process of 18650 cylindrical lithium-ion batteries (LiBs) in NaCl and NaOH solutions and the generation of corrosion products, with the aim of developing a safe and clean discharging system for practical applications. The results show that water electrolysis is the primary reaction during battery immersion in either NaCl or NaOH solutions. Different forms of corrosion occur in each solution. Unlike the NaCl solution, which severely corroded the positive terminal of the battery, resulting in significant amount of solid residue, build-up of fluoride ions, and chlorine gas evolution, in the NaOH solution, a darkened surface of the negative terminal was the only obvious solid product, with no solid residue in the bulk solution, while oxygen gas was evolved. The NaOH solution was found to reduce battery capacity to a residual capacity range of 0–25 mAH after immersing batteries in the solution for 20 h. This value puts the battery in a safe condition for subsequent mechanical treatment. The results indicated that NaOH creates a clean discharging system and can potentially be reused.

Experimental studies on two-phase immersion liquid cooling for Li-ion battery thermal management

The thermal management of lithium-ion batteries (LIBs) has become a critical topic in the energy storage and automotive industries. Among the various cooling methods, two-phase submerged liquid cooling is known to be the most efficient solution, as it delivers a high heat dissipation rate by utilizing the latent heat from the liquid-to-vapor phase change. In this study, a novel two-phase liquid immersion system was proposed, and the cooling performance of an 18650 LIB was investigated to evaluate the effects of thermal management on the performance of the battery pack. Four cooling strategies, namely natural, forced convection, mineral oil (single-phase), and SF33 fluid (two-phase) cooling, were compared under different discharge rates and dynamic load conditions. The results suggest that two-phase immersion cooling with SF33 fluid was highly effective to keep the cell temperature under 34 °C under all tested conditions, and the temperature change of the battery did not exceed 5 °C. A large amount of heat from the battery during high C discharge was absorbed by the boiling of SF33, allowing it to effectively maintain the cell temperature in an optimal temperature range (33–34 °C). Finally, the mechanism of pool heat transfer was determined through visual analysis. Initially, small bubbles appeared near the wires and battery terminals, which acted as gasification cores. Subsequently, small bubbles arose around the surface of the battery body, most of which grew to reach the interface. Eventually, the vapor condensed near the top condenser coils. This study provides a foundation for the further development of direct two-phase liquid-cooling technology, which can be an effective method for enhancing the life and safety of LIBs.

An entropy model for Carreau nanofluid ciliary flow with electroosmosis and thermal radiations: A numerical study.

In order to localize heat production and drug activation, it is possible for drug delivery to make use of nanofluids containing thermal radiation. By limiting the amount of medication that is administered to healthy tissues, this approach increases drug distribution. We explore the effect that thermal radiation has on the flow of a ternary-hybrid nanofluid composed of titanium oxide (TiO2), silica (SiO2), and aluminum oxide (AI2O3). The base liquid that we use for our Carreau constitutive model is blood. Entropy and electroosmosis are both taken into account when the conduit is connected to the battery terminals outside. Following the step of translating the observation model into a wave frame, the physical restrictions of the lubrication theory are used in order to provide a more complete explanation for the wave occurrences. In this work, shooting is used to simulate boundary value issues that are solved with Mathematica NDSolve. The production of the least amount of entropy and a rise in thermodynamic efficiency are achieved by the motion of cilia and elastic electroosmotic pumping. It is also observed that heat transfer is proportional to the length of cilia. Nusselt number is increased by large cilia but skin friction got a reduction.

Mathematical model of ciliary flow and entropy for carreau nanofluid with electroosmosis and radiations in porous medium: A numerical work

Functionalizing the nanoparticles like titanium oxide (TiO2), silica (SiO2), and aluminum oxide (AI2O3) with therapeutic agents like anticancer drugs, antibiotics, or gene therapy agents allow targeted delivery and controlled release. We investigate how thermal radiation in Carreau constitutive model base liquid (blood) affects the flow of a ternary-hybrid nanofluid made of the said particles. Connecting the conduit to battery terminals outside accounts for entropy and electroosmosis. After translating the observation model into a wave frame, lubrication theory's physical limits are used to better explain the wave phenomena. The study uses Mathematica NDSolve to simulate boundary value issues using shooting. The Carreau fluid has a 17–18% higher heat transfer rate than the Williamson fluid, according to the literature. Elastic electroosmotic pumping, cilia motion, and magnetic fields improve fluid transport. Ternary hybrid nanofluids improve transport mechanisms and thermal conductivity. Elastic electroosmotic pumping and cilia motion produce the least entropy and increase thermodynamic efficiency.

On the Usage of Battery Equivalent Series Resistance for Shuntless Coulomb Counting and SOC Estimation

In this paper, a feasibility study of a shuntless coulomb counting method for estimating the state of charge (SOC) of a battery is presented. Contrary to conventional coulomb counting, the proposed method does not require an external resistive shunt; it instead only requires voltage measurements performed on the battery under test while it is operating. The current is measured indirectly using the battery’s equivalent series resistance (ESR). The method consists of a preliminary calibration phase where the ESR and the open-circuit voltage of the battery are measured for different SOCs and stored in look-up tables (LUTs). Then, in the subsequent operational phase, the method uses these LUTs together with the measured voltage at the battery terminals to estimate the SOC. The performance of the proposed method is evaluated on a sample lithium polymer (LiPo) battery, using a realistic current profile derived from the Worldwide Harmonized Light-Duty Vehicles Test Procedure (WLTP). The results of this experimental evaluation demonstrate a SOC estimation root-mean-square error of 0.82% and a maximum SOC error of 1.45%. These results prove that the proposed method is feasible in a practical scenario.

Оценка несущей способности контактного соединения полюсного вывода свинцовой аккумуляторной батареи

Introduction. The data given in the article show that the problem of increase of fire safety at operation of vehicles is actual. The main purpose of the article is to develop a scientifically based method of examination of contact connections of pole terminals of starter batteries, which have signs of high transient resistance or change in geometrical shape in order to find out the reason of damage in the course of fire-technical expertise. Materials and methods. The researches were carried out with the use of a scanning-electron microscope JSM-6390LV with an attachment for energy-dispersive microanalysis. The objects of research were pole terminals of a lead-acid storage battery of European type and their tips. Contact surfaces of the tips were analyzed without preliminary sample preparation. Theoretical background (theory and calculations). A physical and mathematical model of ultimate load-bearing capacity of lead battery terminal, which corresponds to real design, has been developed. On this basis, there is formulated a computational and practical algorithm for expert analysis of its mechanical and geometrical characteristics. The solution has been simplified to short calculating formulas, allowing to estimate the contact load-bearing capacity. The applicability of the developed mathematical model to carrying out fire-technical exami­nations is shown by a concrete example. Results and discussion. Examples are given of car fires, which were caused by loss of load-bearing capacity in the contact of battery terminals with wire-end terminals during in the process of operation. Pictures of the result of high transient resistance on the contact surface and its elemental composition are given. Experimental data confirmed that the transfer of the material of the pole leads to the tips of wires in the form of drops of lead and its layers is a significant forensic feature in determining the cause of the fire. Conclusions. The method of determination of load-bearing capacity of contact of a lead battery pole to the wire end, on the basis of which it is possible to draw a conclusion about participation of great transient resistance in the contact to the subsequent fire, is offered. The data given in the article may be used by specialists during an expert examination of lead battery terminals, seized from places of fires, in order to establish the mechanism of their damage and, finally, the cause of a fire.

Agnostic Battery Management System Capacity Estimation for Electric Vehicles

Battery degradation is a main concern for electric vehicle (EV) users, and a reliable capacity estimation is of major importance. Every EV battery management system (BMS) provides a variety of information, including measured current and voltage, and estimated capacity of the battery. However, these estimations are not transparent and are manufacturer-specific, although measurement accuracy is unknown. This article uses extensive measurements from six diverse EVs to compare and assess capacity estimation with three different methods: (1) reading capacity estimation from the BMS through the central area network (CAN)-bus, (2) using an empirical capacity estimation (ECE) method with external current measurements, and (3) using the same method with measurements coming from the BMS. We show that the use of BMS current measurements provides consistent capacity estimation (a difference of approximately 1%) and can circumvent the need for costly experimental equipment and DC chargers. This data can simplify the ECE method only by using an on-board diagnostics port (OBDII) reader and an AC charger, as the car measures the current directly at the battery terminals.

An Isolated Standalone Photovoltaic-Battery System for Remote Areas Applications

A standalone photovoltaic-battery system (SBPS) for remote areas must be reliable, cost-effective, safe, and designed to extend battery life. A typical configuration of SPBS is non-isolated and uses a dc–dc bidirectional converter for charging and discharging the batteries connected to the dc link. This configuration needs a high-gain dc–dc converter, usually inefficient, to integrate the batteries to the dc link or stack batteries in series to obtain high voltage. This paper proposes connecting the batteries, through a bidirectional low ripple current converter (Cuk), to the terminals of the photovoltaic (PV) panel to solve the problems mentioned above. The Cuk bidirectional converter controls the dc-link voltage by charging/discharging the battery using simple cascade control. In addition to managing the power battery, the continuous currents at the input and output of the converter avoid excessive current oscillations at the PV panels and battery terminals, improving the maximum power point tracking (MPPT) performance and the battery lifetime. The proposed SBPS is composed of a combination of an isolated interleaved boost (IIB) converter, a Cuk bidirectional converter, and a 3-Level T-type (3LT2) Neutral-Point Clamped (NPC) inverter to reduce the number of switches and assure power quality. This configuration provides grounding and isolation between PV panels, battery, and the load. The analysis of power converters that compose the SBPS, the dynamic behavior, and the design procedures are introduced and verified by simulations and experimental results obtained from a Hardware-in-the-Loop (HIL) testing platform.

Tackling the Lead Gremlins: A Response to Take-Home Lead Exposure in a Minnesota Industrial Facility, 2019.

Lead exposure that occurs from contamination inadvertently brought home from a workplace is known as take-home exposure. Take-home exposures are a public health hazard that adversely affects health equity for families and communities. This article describes coordinated action by agencies in Minnesota to curb lead exposure among children of workers at a facility that produces fishing sinkers and battery terminals. (Am J Public Health. 2022;112(S7):S655-S657. https://doi.org/10.2105/AJPH.2022.306982).

Characteristics of Open Circuit Voltage Relaxation in Lithium-Ion Batteries for the Purpose of State of Charge and State of Health Analysis

Open circuit voltage relaxation to a steady state value occurs, and is measured, at the terminals of a lithium-ion battery when current stops flowing. It is of interest for use in determining state of charge and state of health. As voltage relaxation can take several hours, a representative model and curve fitting is necessary for practical usage. Previous studies of lithium-ion voltage relaxation investigate four characteristics: relationship between voltage relaxation magnitude and state of charge; length of relaxation required; model complexity for state of charge estimation; and model complexity for state of health evaluation. However, previous studies have inconsistent methodology or use only one type of lithium-ion cell, making comparison and generalization difficult. To address this, we conducted 3 h and 24 h voltage relaxation experiments over a range of states of charge on three different lithium ion chemistries (nickel cobalt aluminum NCA; nickel manganese cobalt NMC532; lithium iron phosphate LFP) and fitted them with a new voltage relaxation equivalent circuit model. It was found that a 3 h relaxation period was sufficient for NMC and LFP for state of charge and state of health investigations. Voltage relaxation of the NCA cell continued to evolve past 24 h. It was shown that voltage relaxation shape and magnitude changes as a function of state of charge, and the accuracy of estimating state of charge was explored. Strategically choosing a state of charge for state of health assessment can be optimized to accentuate voltage relaxation magnitude and this differs by chemistry. This suggested technique and experimental findings can be paired with battery degradation studies to determine accuracy of assessing state of health.

EIS2MOD: A DRT-Based Modeling Framework for Li-Ion Cells

The correct assessment of battery states is essential to maximize battery pack performances while ensuring reliable and safe operation. This article introduces EIS2MOD, a novel modeling framework for li-ion cells based on distribution of relaxation time. A physically-based electric circuit model is developed starting from electrochemical impedance spectroscopy and open-circuit voltage measurements. Distribution of relaxation time (DRT) is applied to deconvolve the electrochemical phenomena from the EIS. The presented methodology is based on: DRT calculation from EIS; DRT analysis for ECM configuration; and model parameters extraction and fitting. The proposed framework is applied to large format li-ion pouch cells, which are tested over the whole state of charge (SoC) range and a wide temperature range (&#x2212;10 &#x00B0;C to 35 &#x00B0;C). Different current profiles have been tested to validate the model, showing its high accuracy in reproducing the battery cell behavior (e.g., RMSE on the battery terminals voltage lower than 1.50&#x0025; for driving cycle simulations at variable temperature and SoC). An additional advantage of EIS2MOD is its light computational load thus offering an attractive framework for battery management system implementation.

Performance Analysis of VRLA Battery for DC Load at Telecommunication Base Station

The high level of power outage in Sukabumi-Cianjur area has influenced the operations of telecommunication industry in the vicinity. This has shortened the battery life at the Base Station (BTS). This study aims to analyze the performance of a (new) VRLA battery against a DC load (BTS) to support the continuity of BTS operation in case of a power outage. The research method used is a (new) battery charge-discharge procedure. Parameters are analyzed by determining the on-site battery discharge duration, the pressure at the battery terminals between cells during backup, and the capacity of the rectifier module to support fast charging. To support fast charging, the rectifier with the formula N+1 and C-rate is 10% and C15 is 15% of the battery capacity. The internal impedance value is 3.4 mΩ and the battery terminal pressure (torque) is 9-11 N/m. The battery performance analysis of the four BTS shows that two of them managed to do a backup, while the other two did not provide good performance.

Towards robotizing the processes of testing lithium-ion batteries

To boost the circular economy of the electric vehicle battery industry, an accurate assessment of the state of health of retired batteries is essential to assign them an appropriate value in the post automotive market and material degradation before recycling. In practice, the advanced battery testing techniques are usually limited to laboratory benches at the battery cell level and hardly used in the industrial environment at the battery module or pack level. This necessitates developing battery recycling facilities that can handle the assessment and testing undertakings for many batteries with different form factors. Towards this goal, for the first time, this article proposes proof of concept to automate the process of collecting the impedance data from a retired 24kWh Nissan LEAF battery module. The procedure entails the development of robot end-of-arm tooling that was connected to a Potentiostat. In this study, the robot was guided towards a fixed battery module using visual servoing technique, and then impedance control system was applied to create compliance between the end-of-arm tooling and the battery terminals. Moreover, an alarm system was designed and mounted on the robot’s wrist to check the connectivity between a Potentiostat and the battery terminals. Subsequently, the electrochemical impedance spectroscopy test was run over a wide range of frequencies at a 5% state of charge. The electrochemical impedance spectroscopy data obtained from the automated test is validated by means of the three criteria (linearity, causality and stability) and compared with manually collected measurements under the same conditions. Results suggested the proposed automated configuration can accurately accomplish the electrochemical impedance spectroscopy test at the battery module level with no human intervention, which ensures safety and allows this advanced testing technique to be adopted in grading retired battery modules.

Collagen and Carbon-ferrous Nanoparticles Used as a Green Energy Composite Material for Energy Storage Devices

Background:: Chrome shavings, a bioactive material, are generated from tannery as waste material. These chrome shaving can be used for the preparation of many value-added products. Objective:: One such attempt is made to use these chrome shaving wastes as a composite bio-battery to produce DC voltage, an alternate green energy source and cleaner technology. Methods:: Chrome shavings are hydrolyzed to make collagen paste and mixed with the ferrous nanoparticles of Moringa oleifera leaves and Carbon nanoparticles of Onion peels to form electrolyte paste as base. Then, the electrolyte base was added to the aluminum paste and conducting gel, and mixed well to form composite material for bio-battery. Results:: The composite material of bio-battery has been characterized using Scanning Electron Microscopy (SEM), Fourier-Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC) and Thermo Gravimetric Analysis (TGA). Series and parallel circuit testing were done using Copper and Zinc electrodes or Carbon and Zinc electrodes as the battery terminals in the electrolyte paste. The surface area of these electrodes needs standardization from bench to pilot scale. The power generated, for an AA battery size, using a single bio-battery cell has produced a DC voltage of 1.5 V; current of 900 mA. Circuit testing on 1 ml of 80 well-cells connected in series has produced DC output of 18 V and 1100 mA whereas 48 V and 1500 mA were obtained from a series-parallel connection. Conclusion:: The glass transition temperature (Tg) of electrolyte of the bio-battery at 53°C indicated that at this temperature, all the substances present in the bio-battery were well spread and consistently contributed to the electrolyte activity where Fe-C-nano-particles were able to form strong chemical bonds on the flanking hydroxyl group sites of the collagen leading to reduced mobility of polymers and increased Tg. The results instigate promising trends for commercial exploitation of this composite for bio-battery production.