Lithium-ion Polymer Battery Cells Research Articles

Effects of State-of-Charge and Penetration Location on Variations in Temperature and Terminal Voltage of a Lithium-Ion Battery Cell during Penetration Tests

The nail penetration test has been widely adopted as a battery safety test for reproducing internal short-circuits. In this paper, the effects of cell initial State-of-Charge (SOC) and penetration location on variations in cell temperature and terminal voltage during penetration tests are investigated. Three different initial SOCs (10%, 50%, and 90%) and three different penetration locations (one is at the center of the cell, the other two are close to the edge of the cell) are used in the tests. Once the steel cone starts to penetrate the cell, the cell terminal voltage starts to drop due to the internal short-circuit. The penetration tests with higher initial cell SOCs have larger cell surface temperature increases during the tests. Also, the penetration location always has the highest temperature increment during all penetration tests, which means the heat source is always at the penetration location. The absolute temperature increment at the penetration location is always higher when the penetration is close to the edge of the cell, compared to when the penetration is at the center of the cell. The heat generated at the edges of the cell is more difficult to dissipate. Additionally, a battery cell internal short-circuit model with different penetration locations is built in ANSYS Fluent, based on the specifications and experimental data of the tested battery cells. The model is validated with an acceptable discrepancy range by using the experimental data. Simulated data shows that the temperature gradually reduces from penetration locations to their surroundings. The gradients of the temperature distributions are much larger closer to the penetration locations. Overall, this paper provides detailed information on the temperature and terminal voltage variations of a lithium-ion polymer battery cell with large capacity and high power under penetration tests. The presented information can be used for assessing the safety of the onboard battery pack of electric vehicles.

Transient Temperature Distributions on Lithium-Ion Polymer SLI Battery

Lithium-ion polymer batteries currently are the most popular vehicle onboard electric energy storage systems ranging from the 12 V/24 V starting, lighting, and ignition (SLI) battery to the high-voltage traction battery pack in hybrid and electric vehicles. The operating temperature has a significant impact on the performance, safety, and cycle lifetime of lithium-ion batteries. It is essential to quantify the heat generation and temperature distribution of a battery cell, module, and pack during different operating conditions. In this paper, the transient temperature distributions across a battery module consisting of four series-connected lithium-ion polymer battery cells are measured under various charging and discharging currents. A battery thermal model, correlated with the experimental data, is built in the module-level in the ANSYS/Fluent platform. This validated module thermal model is then extended to a pack thermal model which contains four parallel-connected modules. The temperature distributions on the battery pack model are simulated under 40 A, 60 A, and 80 A constant discharge currents. An air-cool thermal management system is integrated with the battery pack model to ensure the operating temperature and temperature gradient within the optimal range. This paper could provide thermal management design guideline for the lithium-ion polymer battery pack.

Influence of deep sea environment on the performance of a LiFePO4 polymer battery

A lithium-ion polymer battery cell is an ideal energy source for underwater vehicles due to its high energy density and small volume. However, the performance of lithium-ion batteries in a 10 000 m deep sea is still unknown and is of particular concern in the design of 10 000 m autonomous remote vehicles (ARVs). In this paper, we explore how the external characterizing parameters of a LiFePO4 polymer battery during discharge are affected by a high pressure of 100 MPa and low temperature of 3 °C for simulating the conditions experienced in a 10 000 m deep sea environment. An unscented Kalman filter (UKF) algorithm is applied to estimate the state of charge (SoC) of a battery to investigate the influence of high hydrostatic pressure on SoC estimation due to changes in parameters. The results indicate that the LiFePO4 polymer battery works under 100 MPa hydrostatic pressure, but its parameters change obviously and influence SoC estimation. SoC estimation accuracy was improved through compensating the functions of open circuit voltage (OCV) versus the state of charge (OCV-SoC) of the battery in a 100 MPa hydrostatic pressure and a low temperature environment.

A Novel Dual H Infinity Filters Based Battery Parameter and State Estimation Approach for Electric Vehicles Application

Abstract An accurate battery parameter and state estimation method is one of the most significant and difficult techniques to promote the commercialization of electric vehicles. This paper tries to make three aspects of effort. First, to avoid the battery state-of-charge (SoC) estimation inaccuracy brought by the variation of the model parameter under different aging level and operation condition, a novel dual H infinity filters was proposed and employed to execute the online measured data based battery parameter and SoC estimation. Second, to overcome the drawback of the H infinity filters are sensitive to their initial noise information. An adaptive H infinity filter employing the covariance matching approach was proposed and applied to realize a robust SoC estimation. Last, the accurate estimate of battery parameter and SoC were obtained real-timely through model-based dual H infinity filters. A systematic evaluation on the different algorithms based SoC estimation was carried out. Experimental results on various degradation states of lithium-ion polymer battery cells further verified the feasibility of the proposed approach.

A data-driven adaptive state of charge and power capability joint estimator of lithium-ion polymer battery used in electric vehicles

An accurate SoC (state of charge) and SoP (state of power capability) joint estimator is the most significant techniques for electric vehicles. This paper makes two contributions to the existing literature. (1) A data-driven parameter identification method has been proposed for accurately capturing the real-time characteristic of the battery through the recursive least square algorithm, where the parameter of the battery model is updated with the real-time measurements of battery current and voltage at each sampling interval. (2) An adaptive extended Kalman filter algorithm based multi-state joint estimator has been developed in accordance with the relationship of the battery SoC and its power capability. Note that the SoC and SoP can be predicted accurately against the degradation and various operating environments of the battery through the data-driven parameter identification method. The robustness of the proposed data-driven joint estimator has been verified by different degradation states of lithium-ion polymer battery cells. The result indicates that the estimation errors of voltage and SoC are less than 1% even if given a large erroneous initial state of joint estimator, which makes the SoP estimate more accurate and reliable for the electric vehicles application.

A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion polymer battery in electric vehicles

Accurate estimations of battery parameter and state play an important role in promoting the commercialization of electric vehicles. This paper tries to make three contributions to the existing literatures through advanced time scale separation algorithm. (1) A lumped parameter battery model was improved for achieving accurate voltage estimate against different battery aging levels through an electrochemical equation, which has enhanced the relationship of battery voltage to its State-of-Charge (SoC) and capacity. (2) A multi-scale extended Kalman filtering was proposed and employed to execute the online measured data driven-based battery parameter and SoC estimation with dual time scales in regarding that the slow-varying characteristic on battery parameter and fast-varying characteristic on battery SoC, thus the battery parameter was estimated with macro scale and battery SoC was estimated with micro scale. (3) The accurate estimate of battery capacity and SoC were obtained in real-time through a data-driven multi-scale extended Kalman filtering algorithm. Experimental results on various degradation states of lithium-ion polymer battery cells further verified the feasibility of the proposed approach.

Comparison, Selection, and Parameterization of Electrical Battery Models for Automotive Applications

This paper describes the comparison and parameterization process of dynamic battery models for cell and system simulation. Three commonly used equivalent circuit battery models are parameterized using a numeric optimization method and basic electrical tests with a lithium-ion polymer battery cell. The maximum model performance is investigated, and the parameterized models are compared regarding the parameterization effort and the model accuracy. For the model with the best tradeoff between the parametrization effort and the model accuracy, a reasonable simplification of the parameterization process is presented. This model is parameterized with the simplified parameterization process and, finally, validated by using a current profile obtained from an electric vehicle simulation performing a real-life driving cycle.

Investigation of lithium-ion polymer battery cell failure using X-ray computed tomography

The paper presents the first application of laboratory X-ray μCT for post-mortem analysis of a failed lithium-ion polymer battery pouch cell. Analysis of the μCT data allowed quantification of the physical distortion within the individual cell layers of both an untested and failed cell. In the failed cell, the maximum separation of the electrode assemblies was measured in each direction (XY = 833 μm, YZ = 787 μm), representing a significant increase from the untested cell, where the spacing was below 43 μm. Deformation was more prominent in the central region of the cell since both ends of the battery electrodes remained tightly clamped even after failure. Based on the visually observed volume expansion and the deformation of the cell architecture observed by μCT we conclude that the deformation was caused by pressure build up as a result of gas generation, which could have arisen from a short circuit in the cell.

Mechanical durability and electrical durability of an aluminium-laminated lithium-ion polymer battery pack for a hybrid electric vehicle

Lithium-ion polymer batteries of aluminium-laminated packaging structure have advantages in terms of thermal characteristics and safety but have a weak configuration with respect to external forces compared with other types of cells such as cylindrical and prismatic cells. Thus it is important to protect the batteries of the aluminium-laminated packaging structure under the severe conditions encountered in vehicle operation where excessive mechanical impacts and vibrations may affect the battery system. In this work, an energy storage system for a hybrid electric vehicle (HEV) has been developed using lithium-ion polymer battery cells with an aluminium-laminated packaging structure and has been tested for structural and electrical durabilities. The test results of combined accelerated vibration and charge discharge cycling are presented to prove that the battery pack has the durability to satisfy vehicle standards. Three different types of test method have been applied to evaluate the mechanical and electrical durabilities. It was observed that the HEV battery pack satisfied the durability standards required for vehicle applications. The results imply that an aluminium-laminated cell packaging structure can be a competitive option for physical configuration of cells for vehicle applications.