Characterization and modeling of a hybrid electric vehicle lithium-ion battery pack at low temperatures

Although lithium-ion batteries have penetrated hybrid electric vehicles (HEVs) and pure electric vehicles (EVs), they suffer from significant power capability losses and reduced energy at low temperatures. To evaluate those losses and to make an efficient design, good models are required for system simulation. Subzero battery operation involves nonclassical thermal behavior. Consequently, simple electrical models are not sufficient to predict bad performance or damage to systems involving batteries at subzero temperatures. This paper presents the development of an electrical and thermal model of an HEV lithium-ion battery pack. This model has been developed with MATLAB/Simulink to investigate the output characteristics of lithium-ion batteries over the selected operating range of currents and battery capacities. In addition, a thermal modeling method has been developed for this model so that it can predict the battery core and crust temperature by including the effect of internal resistance. First, various discharge tests on one cell are carried out, and then, cell's parameters and thermal characteristics are obtained. The single-cell model proposed is shown to be accurate by analyzing the simulation data and test results. Next, real working conditions tests are performed, and simulation calculations on one cell are presented. In the end, the simulation results of a battery pack under HEV driving cycle conditions show that the characteristics of the proposed model allow a good comparison with data from an actual lithium-ion battery pack used in an HEV. © 2015 IEEE

SoC estimation for lithium-ion batteries : review and future challenges

ABSTRACT: Energy storage emerged as a top concern for the modern cities, and the choice of the lithium-ion chemistry battery technology as an effective solution for storage applications proved to be a highly efficient option. State of charge (SoC) represents the available battery capacity and is one of the most important states that need to be monitored to optimize the performance and extend the lifetime of batteries. This review summarizes the methods for SoC estimation for lithium-ion batteries (LiBs). The SoC estimation methods are presented focusing on the description of the techniques and the elaboration of their weaknesses for the use in on-line battery management systems (BMS) applications. SoC estimation is a challenging task hindered by considerable changes in battery characteristics over its lifetime due to aging and to the distinct nonlinear behavior. This has led scholars to propose different methods that clearly raised the challenge of establishing a relationship between the accuracy and robustness of the methods, and their low complexity to be implemented. This paper publishes an exhaustive review of the works presented during the last five years, where the tendency of the estimation techniques has been oriented toward a mixture of probabilistic techniques and some artificial intelligence

Lithium-ion battery aging experiments at subzero temperatures and model development for capacity fade estimation

Lithium-ion (Li-ion) batteries widely used in electric vehicles (EVs) and hybrid EVs (HEVs) are insufficient for vehicle use after they have degraded to 70% to 80% of their original capacity. Battery lifespan is a large consideration when designing battery packs for EVs/HEVs. Aging mechanisms, such as metal dissolution, growth of the passivated surface film layer on the electrodes, and loss of both recyclable lithium ions, affect the longevity of the Li-ion battery at higherature operations. Even vehicle maneuvers at low temperatures (T<0°C)contribute to battery lifetime degradation, owing to the anode electrode vulnerability to other degradation mechanisms such as lithium plating. Nowadays, only a few battery thermal management schemes have properly considered lowerature degradation. This is due to the lack of studies on aging of Li-ion batteries at sub-zero temperature. This paper investigates how load cycle and calendar life properties affect the lifetime and aging processes of Li-ion cells at low temperatures. Accelerated aging tests were used to determine the effect of the ambient temperature on the performance of three 100-Ah LiFeMnP04 Li-ion cells. Two of them were aged through a normalized driving cycle at two temperature tests (-20°C and 25°C). The calendar test was carried out on one single battery at -20 °C and mid-range of state of charge (50%). Their capacities were continuously measured every two or three days. An aging model is developed and added to a preliminary single-cell electrothermal model to establish, in future works, a thermal strategy capable of predicting how the cell ages. This aging model was then validated by comparing its predictions with the aging data obtained from a cycling test at 0 °C. © 1967-2012 IEEE

Constrained generalized predictive control of battery charging process based on a coupled thermoelectric model

Battery temperature is a primary factor affecting the battery performance, and suitable battery temperature control in particular internal temperature control can not only guarantee battery safety but also improve its efficiency. This is however challenging as current controller designs for battery charging have no mechanisms to incorporate such information. This paper proposes a novel battery charging control strategy which applies the constrained generalized predictive control (GPC) to charge a LiFePO₄ battery based on a newly developed coupled thermoelectric model. The control target primarily aims to maintain the battery cell internal temperature within a desirable range while delivering fast charging. To achieve this, the coupled thermoelectric model is firstly introduced to capture the battery behaviours in particular SOC and internal temperature which are not directly measurable in practice. Then a controlled auto-regressive integrated moving average (CARIMA) model whose parameters are identified by the recursive least squares (RLS) algorithm is developed as an online self-tuning predictive model for a GPC controller. Then the constrained generalized predictive controller is developed to control the charging current. Experiment results confirm the effectiveness of the proposed control strategy. Further, the best region of heat dissipation rate and proper internal temperature set-points are also investigated and analysed

A review of thermal management for Li-ion batteries: Prospects, challenges, and issues

Li-ion batteries are essential component in the current generation of electric vehicles. However, further pushing electric vehicles are concerned with battery life. Since the temperature dictates battery lifetime, it is crucial to manage the heat and keep the temperature at an acceptable range within the battery pack. The benefit of a cooling system is to prevent the premature degradation of battery life. This paper provides a critical review of the so far thermal management strategy dealing with temperature within the cells, module, and packs. This paper reviews the advantages and disadvantages of state of the art (traditional) thermal cooling system. In this paper, we have reviewed separately cell, module, and pack level cooling system. The battery thermal modeling techniques and cooling system design challenges are also reviewed. This paper also reviews the future cooling system for future vehicles with rising fast charge rate and these techniques can improve the limitations of the traditional cooling system. This paper also suggests the best suitable and economically viable technology for the upcoming EVs issues

Latent Thermal Energy Storage Technologies and Applications: A Review

The achievement of European climate energy objectives which are contained in the European Union's (EU) “20-20-20” targets and in the European Commission's (EC) Energy Roadmap 2050 is possible, among other things, through the use of energy storage technologies. The use of thermal energy storage (TES) in the energy system allows to conserving energy, increase the overall efficiency of the systems by eliminating differences between supply and demand for energy. The article presents different methods of thermal energy storage including sensible heat storage, latent heat storage and thermochemical energy storage, focusing mainly on phase change materials (PCMs) as a form of suitable solution for energy utilisation to fill the gap between demand and supply to improve the energy efficiency of a system . PCMs allow the storage of latent thermal energy during phase change at almost stable temperature. The article presents a classification of PCMs according to their chemical nature as organic, inorganic and eutectic and by the phase transition with their advantages and disadvantages. In addition, different methods of improving the effectiveness of the PCM materials such as employing cascaded latent heat thermal energy storage system, encapsulation of PCMs and shape-stabilisation are presented in the paper. Furthermore, the use of PCM materials in buildings, power generation, food industry and automotive applications are presented and the modelling tools for analysing the functionality of PCMs materials are compared and classified

Developments of electric cars and fuel cell hydrogen electric cars

The world continues to strive in the search for clean power sources to run the millions of different vehicles on the road on daily basis as they are the main contributors to toxic emissions releases from internal combustion engines to the atmosphere. These toxic emissions contribute to climate change and air pollution and impact negatively on people's health. Fuel cell devices are gradually replacing the internal combustion engines in the transport industry. Some notable challenges of the PEMFC technology are discussed in this paper. High costs, low durability and hydrogen storage problems are some of the major obstacles being examined in this investigation. The paper explores the latest advances in electric cars technology and their design specifications. The study also compares the characteristics and the technologies of the three types of electric cars now available in the market.interna

Comparison of two levels of cell models for an EV current cycle

International audienceThis paper studies the effect of the granularity of acell model on the voltage accuracy. A multi-coupled cell modelwith varying parameters is compared with a simpler one(varying voltage source and equivalent series resistance). Thefirst model implies a very long and complex characterizationprocess. The second one is very simple. Experiments areperformed at different temperatures by applying a currentprofile corresponding to a driving cycle of an electric vehicle.Experimental results show both models can be used for 25°Cand 10 °C ambient temperatures with reasonable accuracy.Nevertheless, when the temperature is cold the multi-coupledmodel is more accurate