LiFePO4 Battery Pack Research Articles

Recognition of battery aging variations for LiFePO4 batteries in 2nd use applications combining incremental capacity analysis and statistical approaches

To assess the economic benefits of battery reuse, the consistency and aging characteristics of a retired LiFePO4 battery pack are studied in this paper. The consistency of battery modules is analyzed from the perspective of the capacity and the internal resistance. Test results indicate that battery module parameter dispersion increases along with battery aging. However, battery modules with better capacity consistency doesn't ensure better resistance consistency. Then the aging characteristics of the battery pack are analyzed and the main results are as follow: (1) Weibull and normal distribution are feasible to fit the capacity and resistance distribution of battery modules respectively; (2) SOC imbalance is the dominating factor in the capacity fading process of the battery pack; (3) By employing the incremental capacity (IC) and IC peak area analysis, a consistency evaluation method representing the aging mechanism variations of the battery modules is proposed and then an accurate battery screening strategy is put forward. This study not only provides data support for evaluating economic benefits of retired batteries but also presents a method to recognize the battery aging variations, which is helpful for rapid evaluation and screening of retired batteries for 2nd use.

Novel active LiFePO4 battery balancing method based on chargeable and dischargeable capacity

Abstract A lithium iron phosphate battery (LiFePO4) pack is one of the main power resources for electric vehicles and the non-uniformity of cells in the battery pack has become the bottleneck to improve the pack capacity. An active balancing method based on chargeable and dischargeable capacities, derived from the dynamically estimated state of charge (SOC) and capacity in the pack, is proposed to tackle this problem in both the charging and discharging processes. To determine the current of each cell in balancing operation, one extra current sensor is added with a chosen flyback balancing circuit. The balancing simulation of a LiFePO4 battery pack has been conducted in the moderate and severe capacity imbalance scenarios. The simulation results show that the proposed battery balancing method has better performance than the other balancing methods based on voltage or SOC in increasing the charged and discharged pack capacity in the charging and discharging process.

Thermal management of a LiFePO4 battery pack at high temperature environment using a composite of phase change materials and aluminum wire mesh plates

One of the most significant factors affecting the performance and life cycle of lithium-ion batteries is temperature. During the charging and discharging processes a large amount of heat is continuously generated inside the cells causing an increase in surface temperature which results life time deterioration to the pack’s performance and power supply and in severe conditions causing an explosion inside the car especially in the hot temperature regions. In this study a composite of a phase change material and aluminum wire mesh plates has been used for the thermal management system of LiFePO4 pack to control the temperature rise of the batteries at high temperature regions (50–55°C). Poly Ethylene Glycol 1000 (PEG1000) with melting point of 35–40°C has been used as a phase change material. Aluminum wire mesh plates have been applied to the PCM for thermal conductivity enhancement and also to improve the temperature uniformity of the system. Preliminary experimental runs have been performed in charge and discharge of the batteries at different rates of 1–3C to obtain the maximum surface temperature of the cells. Due to the page limit of the manuscript, only the discharge results are presented here. A mathematical model has been developed for one of the cells in COMSOL ver. 5.1 and the results of the model have been verified by the experimental data obtained at different conditions. The results show that using the PCM and aluminum wire mesh plates between the cells can reduce the surface temperature significantly and causes better performance for the battery pack. The maximum cell surface temperatures at ambient temperature condition have been reduced by 19%, 21%, and 26% for the rates of 1C, 2C, and 3C respectively.

A Comparative Study Based on the Least Square Parameter Identification Method for State of Charge Estimation of a LiFePO4 Battery Pack Using Three Model-Based Algorithms for Electric Vehicles

Battery energy storage management for electric vehicles (EV) and hybrid EV is the most critical and enabling technology since the dawn of electric vehicle commercialization. A battery system is a complex electrochemical phenomenon whose performance degrades with age and the existence of varying material design. Moreover, it is very tedious and computationally very complex to monitor and control the internal state of a battery’s electrochemical systems. For Thevenin battery model we established a state-space model which had the advantage of simplicity and could be easily implemented and then applied the least square method to identify the battery model parameters. However, accurate state of charge (SoC) estimation of a battery, which depends not only on the battery model but also on highly accurate and efficient algorithms, is considered one of the most vital and critical issue for the energy management and power distribution control of EV. In this paper three different estimation methods, i.e., extended Kalman filter (EKF), particle filter (PF) and unscented Kalman Filter (UKF), are presented to estimate the SoC of LiFePO4 batteries for an electric vehicle. Battery’s experimental data, current and voltage, are analyzed to identify the Thevenin equivalent model parameters. Using different open circuit voltages the SoC is estimated and compared with respect to the estimation accuracy and initialization error recovery. The experimental results showed that these online SoC estimation methods in combination with different open circuit voltage-state of charge (OCV-SoC) curves can effectively limit the error, thus guaranteeing the accuracy and robustness.

State of health estimation algorithm of LiFePO4 battery packs based on differential voltage curves for battery management system application

This paper discusses a novel differential voltage curve capacity estimation to determine the state of health of LiFePO4 cells. Differential voltage curves are used because of their ability to detect and quantify degradation mechanisms. The estimation is carried out through partial charging or discharging tests, and is specifically designed for battery management systems, due to the trade off between accuracy and low computational effort. This means the method can be effectively executed online, in a real application. The technique is also able to accurately detect the end of life of the cells.Aging datasets of 18 cells with identical chemistry were used for both parametrization and validation. The cells were subjected to a wide range of cycling and storage conditions, including temperature, state of charge, charging and discharging rate, depth of discharge and state of health. The performance and robustness of the estimation are validated by means of the degradation datasets from more than 25 different scenarios at the cell and battery pack level. The related results indicate that the proposed health management strategy has an average relative error of 1.5% at the battery pack level.

On-board state of health estimation of LiFePO4 battery pack through differential voltage analysis

Battery state of health (SOH) estimation is a crucial challenge for electric vehicles due to the complicated aging mechanism of a battery. In this paper, a new method for battery SOH estimation is proposed using the location interval between two inflection points or the transformation parameter of the differential voltage (DV) curve. And a new algorithm to obtain the DV curve according to the center least squares method is presented. Four LiFePO4 battery cells in different aging states are tested to validate the proposed method. Results show that the linear regression of the location interval between two inflection points versus the battery capacity from one single battery cell is able to evaluate the SOH of other three battery cells within 2% error bound. Transforming the measured DV curve to be congruent with the initial DV curve provided by the manufacturer, battery cell SOH can be estimated according to the transformation parameter with the error being within 2.5%. Furthermore, a battery pack SOH monitoring framework is inferred from the inflection point location and the transformation parameter of the DV curve to realize battery pack SOH estimation.

Inline state of health estimation of lithium-ion batteries using state of charge calculation

The determination of state-of-health (SOH) and state-of-charge (SOC) is challenging and remains as an active research area in academia and industry due to its importance for Li-ion battery applications. The estimation process poses more challenges after substantial battery aging. This paper presents an inline SOH and SOC estimation method for Li-ion battery packs, specifically for those based on LiFePO4 chemistry. This new hybridized SOC and SOH estimator can be used for battery packs. Inline estimated model parameters were used in a compounded SOC + SOH estimator consisting of the SOC calculation based on coulomb counting method as an expedient approach and an SOH observer using an extended Kalman filter (EKF) technique for calibrating the estimates from the coulomb counting method. The algorithm's low SOC and SOH estimation error, fast response time, and less-demanding computational requirement make it practical for on-board estimations. The simulation and experimental results, along with the test bed structure, are presented to validate the proposed methodology on a single cell and a 3S1P LiFePO4 battery pack.

Assessment of the forced air-cooling performance for cylindrical lithium-ion battery packs: A comparative analysis between aligned and staggered cell arrangements

An appropriate cell arrangement plays significant role to design a highly efficient cooling system for the lithium-ion battery pack. This paper performs a comparative analysis of thermal performances on different arrangements of cylindrical cells for a LiFePO4 battery pack. A thermal model for the battery pack is developed and is solved in couple with the governing equations of fluid flow in the numerical simulations. The experiments for model validation are conducted on a single cell of the battery pack with forced-air cooling system. The effects of longitudinal and transverse spacing on the cooling performances are analyzed for the battery pack with the aligned and the staggered arrays. Under a specified flow rate of cooling air, the maximum temperature rise is proportional to the longitudinal interval for the staggered arrays, while it is in inverse for the aligned arrangement. Increasing the transverse interval leads to the increase of the battery temperature rise for both aligned and staggered arrangements. By trade-off the design requirements (maximum temperature rise, temperature uniformity, power requirement and cooling index), an appropriate solution in term of the optimal combination of the longitudinal interval, transverse interval, and air inlet width is obtained for the aligned arrangement.

A LiFePO4 battery pack capacity estimation approach considering in-parallel cell safety in electric vehicles

In electric vehicles (EVs), several battery cells are connected in parallel to establish a battery module. The safety of the battery module is influenced by inconsistent battery cell performance which causes uneven currents flowing through internal in-parallel battery cells. A battery cell model is developed based on the Matlab–Simscape platform and validated by tests. The battery cell model is used to construct simulation models for analyzing the effect of battery cell inconsistency on the performance of an in-parallel battery module. Simulation results indicate that the state-of-charge (SOC) of a battery module cannot characterize the SOC of ALL the internal battery cells in the battery module. When the battery management system (BMS) controls the end-of-charge (EOC) time according to the SOC of a battery module, some internal battery cells are over-charged. To guarantee the safety of ALL battery cells through the whole battery life, a safety EOC voltage of the battery module should be set according to the number of battery cells in the battery module and the applied charge current. Simulations reveal that the SOC of the “normal battery module” is related to its charge voltage when aged battery module is charged to the EOC voltage. Then, a function describing their relationship is established. Both the capacity and the charge voltage shift are estimated by comparing the measured voltage-to-capacity curve with the standard one provided by the manufactory. A battery pack capacity estimation method is proposed according to the SOC and the capacity of the “normal battery module”. Experimental results show that battery pack capacity estimation difference between the proposed method and the standard current integration method is to within 0.35%.

Design and Evaluation of a Fully Implantable Control Unit for Blood Pumps.

As the number of donor hearts is limited while more and more patients suffer from end stage biventricular heart failure, Total Artificial Hearts become a promising alternative to conventional treatment. While pneumatic devices sufficiently supply the patients with blood flow, the patient's quality of life is limited by the percutaneous pressure lines and the size of the external control unit. This paper describes the development of the control unit of the ReinHeart, a fully implantable Total Artificial Heart. General requirements for any implantable control unit are defined from a technical and medical point of view: necessity of a Transcutaneous Energy Transmission, autonomous operation, safety, geometry, and efficiency. Based on the requirements, a prototype is designed; it incorporates a LiFePo4 battery pack with charger, a rectifier for transcutaneous energy transmission, the motor's driver electronics, and a microcontroller which monitors and controls all functions. In validation tests, the control unit demonstrated a stable operation on TET and battery supply and a safe switching from one supply to the other. The overall mean efficiency is 14% on TET and 22% on battery supply. The control unit is suitable for chronic animal trials of the ReinHeart.

Experiment and simulation of a LiFePO4 battery pack with a passive thermal management system using composite phase change material and graphite sheets

A passive thermal management system (TMS) for LiFePO4 battery modules using phase change material (PCM) as the heat dissipation source to control battery temperature rise is developed. Expanded graphite matrix and graphite sheets are applied to compensate low thermal conductivity of PCM and improve temperature uniformity of the batteries. Constant current discharge and mixed charge–discharge duties were applied on battery modules with and without PCM on a battery thermal characteristics test platform. Experimental results show that PCM cooling significantly reduces the battery temperature rise during short-time intense use. It is also found that temperature uniformity across the module deteriorates with the increasing of both discharge time and current rates. The maximum temperature differences at the end of 1C and 2C-rate discharges are both less than 5 °C, indicating a good performance in battery thermal uniformity of the passive TMS. Experiments on warm-keeping performance show that the passive TMS can effectively keep the battery within its optimum operating temperature for a long time during cold weather uses. A three dimensional numerical model of the battery pack with the passive TMS was conducted using ANSYS Fluent. Temperature profiles with respect to discharging time reveal that simulation shows good agreement with experiment at 1C-discharge rate.

A Novel Method to Estimate the State of Health of each Cell in Battery Pack

In order to estimate the state of health (SOH) of each cell in the battery pack, polarization resistance and ohmic resistance were analyzed in the aging process of the battery pack. Accelerating aging test for the battery was done, quantitative relationship between the ohmic resistance and the capacity aging was obtained, a method of relative state of health (RSOH) evaluation was proposed accordingly, Experiments on the LiFePO4 battery pack which is connected in series by 100 cells have been taken, the experimental results show that the evaluation method of RSOH can evaluate the cells SOH accurately and is not limited by the operating conditions.

Proposal and Validation of a SOC Estimation Algorithm of LiFePO4 Battery Packs for Traction Applications

An accurate onboard State-of-Charge (SOC) estimation is one of the key functions a Battery Management System (BMS) has to perform in order to provide the optimal performance management of the battery system under control. In this framework, this paper presents a proposal of an Enhanced Coulomb Counting (CC) State-of-Charge estimation algorithm based on Constant Voltage Charge Detection (CVCD) and Open Circuit Voltage (OCV) model for LiFePO4 batteries. Designed for onboard BMS implementation, it is characterized by its simplicity and operability in wide operating conditions (under diverse load profiles, temperatures, SOC ranges, etc.). The description of the algorithm at both, cell and battery-module level is detailed in the paper. Furthermore, its on-line experimental validation and scope determination is tested under three different traction applications and cell specimens in an own-developed real time validation platform: 2.5 Ah cells (Type A) in a residential elevator application, 8 Ah cells (Type B) in a pure electric on-road vehicle application and 100 Ah cells (Type C) in an electric railway vehicle application. According to the achieved results, the accuracy and versatility of the algorithm for different operating scenarios is certainly proven. In the worst case scenario the algorithm is capable of keeping the SOC estimation of the system under test stabilized around 5% of error.

Cell state-of-charge inconsistency estimation for LiFePO4 battery pack in hybrid electric vehicles using mean-difference model

Identification of cell SOC (state-of-charge) inconsistency for LiFePO4 battery packs is challenging due to the demanding conditions in hybrid electric vehicles (HEVs) and the relatively flat SOC–OCV (open circuit voltage) curve of LiFePO4 cells compared to others. We experimentally investigate cell voltages in a small battery pack and propose a Mean-plus-Difference Model (M+D Model). The M+D Model uses a cell mean model (CMM) representing the overall performance of the pack in high frequency. Meanwhile cell voltage differences (CVDs) between cells and the “mean cell” are studied by a cell difference model (CDM) in low frequency. A CDM considering SOC and internal resistance differences is subsequently presented and OCV differences are estimated. We further propose an SOC strategy to accurately identify cell SOC inconsistency by intermittently lowering pack SOC to 30% during HEV operation. Finally we discover that SOC differences can be determined with estimated OCV differences using SOC-difference/OCV-difference curve. The proposed method is verified by simulation and experiment. With the proposed method, LiFePO4 cell SOC inconsistency can be precisely estimated with existing measuring technology during HEV operating and cell equalization can be ultimately implemented.

Hybridization of the lithium energy storage for an urban electric vehicle

Abstract This paper discusses benefits of introducing an ultracapacitor (UC) bank into a battery electric vehicle (BEV) powertrain. The case of 12kWh LiFePO4 battery pack is studied quantitatively. Simulation results refer, inter alia, to three main scenarios: fresh cells, half-used battery cells, and half-used ultracapacitors and batteries. Thermal modeling is incorporated into the simulation. Data from real world are considered: various driving cycles recorded using GPS receiver (incl. elevation), discharge curves from battery manufacturer, and UC equivalent series resistance (ESR) variations due to cycling according to real data reported in papers. Cost, as well as gravimetric and volumetric issues are presented. The key decisions referring to an energy storage for BEV being currently designed within the frame of ECO-Mobility Project are highlighted.

A New State of Charge Estimation Method for LiFePO4 Battery Packs Used in Robots

The accurate state of charge (SOC) estimation of the LiFePO4 battery packs used in robot applications is required for better battery life cycle, performance, reliability, and economic issues. In this paper, a new SOC estimation method, “Modified ECE + EKF”, is proposed. The method is the combination of the modified Equivalent Coulombic Efficiency (ECE) method and the Extended Kalman Filter (EKF) method. It is based on the zero-state hysteresis battery model, and adopts the EKF method to correct the initial value used in the Ah counting method. Experimental results show that the proposed technique is superior to the traditional techniques, such as ECE + EKF and ECE + Unscented Kalman Filter (UKF), and the accuracy of estimation is within 1%.

LiFePO4 battery pack capacity estimation for electric vehicles based on charging cell voltage curve transformation

Because of the diversiform driving conditions and the cell variations, it is difficult to accurately determine battery pack capacities in electric vehicles (EVs) by model prediction or direct measurement. This paper studies the charging cell voltage curves (CCVC) for the estimation of the LiFePO4 battery pack capacities in EVs. We propose the uniform CCVC hypothesis and estimate cell capacities by overlapping CCVCs using CCVC transformation. CCVCs of two LiFePO4 cells with large capacity difference are used to verify the hypothesis. We further develop an equivalent simplified approach using voltage-capacity rate curve (VCRC) and implement Genetic Algorithm (GA) to find the optimum transformation parameter for overlapping VCRCs. A small battery pack with four LiFePO4 cells in series is employed to verify the method and the result shows that the estimation errors of both pack capacity and cell capacities are less than 1%. With the proposed method, the battery pack capacity can be precisely estimated which could be used for the driving range prediction. Meanwhile, the estimated cell capacities in battery packs will significantly support the study of cell degradation and cell variations in vehicle driving conditions.

Criterion of Constant Current Charging End for Lithium Iron Phosphate Batteries

A battery management system (BMS) for lithium iron phosphate (LiFePO4) battery pack is built based on charge and discharge characteristics of the batteries. Charge experiments have been performed at different charge currents. The results indicate that charge voltage curves of the batteries are not the same at different charge currents, Ah capacity change of unit voltage and state of charge (SOC) have a certain relationship in the charging process. Based on these results, a charge method for LiFePO4 battery pack is proposed. By this charge management method, the battery pack can be quickly charged into the most capacity by constant current. At the same time, this method can slow the rate of the battery pack capacity attenuation and extend the cycle life of the battery pack.