Fig 3 - uploaded by Serkan Dusmez
Content may be subject to copyright.
Source publication
Electric vehicles (EVs) have been considered as one of the effective solutions to current energy and environment concerns. One of the challenges regarding the energy storage system (ESS) of today's electric vehicles, which are batteries, is the capacity fade. It is of great importance to identify and analyze the factors contributing to the capacity...
Context in source publication
Context 1
... on these thermal analyses, the electro-thermal model has been added to the original LiFePO 4 battery cell model as shown in Fig. 3. Once battery cell current is determined, SOC for the next step can be easily calculated. Hence, charge/discharge current and terminal voltage forms a closed recurring loop. Supplying the charge/discharge current and the estimated SOC to electro-thermal model as inputs, temperature of a battery cell can be estimated, which will be used ...
Similar publications
The condition monitoring and fault diagnosis of the lithium-ion battery system are crucial issues for electric vehicles. The shocks, blows, twists, and vibrations during the electric vehicle driving process may cause the insulation fault. In order to ensure the safety of the drivers and passengers, a real-time monitor to detect the insulation state...
Citations
... Due to limited resources of fuels, huge cost and GHE are the causes for transformation of traditional transportation to sustainable by using EV (Tremblay and Dessaint, 2009). In EV ESs is playing very important role and out of many storage systems available (Shepherd, 1965;Shen et al., 2013;Miao et al., 2019;Casacca, 1992), battery is most reliable one. Most suitable, most reliable and more flexible to recharge the battery is nothing but the secondary battery, i.e., rechargeable battery. ...
... Hence to maintain the stability during the running operation of EV, ESs ensures the tolerable values of performance parameters by maintaining the stability, reliability and optimum operation of EV. Hence by proper planning and selection of battery above mentioned parameters can be enhanced (Shen et al., 2013). Electro mobility needs lightweight batteries which are having enough capacity to fulfil the need under fast charging and discharging mode of operation. ...
This paper explores the integration of on-grid renewable energy with battery storage to improve consumers' comfort. Demand response (DR) programs are utilized to balance power supply and demand, offering consumers three response options: reducing consumption, shifting consumption, or utilizing on-site generation. However, these options may temporarily affect comfort. To address this, on-site generation through renewable energy integration has gained attention for its environmental and economic advantages. The study aims to demonstrate an environmentally friendly renewable integration system that resolves electrical power problems, ensures consumer comfort, and provides pollution-free energy. The proposed system primarily relies on solar panels with batteries as backup. Optimization is conducted using the HOMER software, and the system design represents a novel approach for the selected site. Simulation results indicate that the proposed approach significantly enhances consumer satisfaction and lowers energy costs in the absence of DR programs. This research presents a comprehensive analysis of the integration approach, emphasizing its benefits for consumers and the environment. By combining renewable energy integration and battery storage, it contributes to sustainable and comfortable energy solutions for consumers.
... In addition, some studies show the integration of two or three types of models for the simulation of LIBs. Looking at some examples of the Electro-Thermal Aging Models, Shen et al. [8] developed a model to estimate the SoC of the cell, the internal cell temperature and the battery lifetime. The impact of various factors such as C-rate of charge and discharge, temperature, maximum discharge current and Depth of Discharge (DoD), cycle time and their effects on the loss of battery cell capacity were investigated and studied. ...
The monitoring and modelling of the Li-Ion Batteries behaviour is still a major technical challenge due to the non-linearities and coupled phenomena that determine their operation. These Li-Ion Batteries can consist of thousands of cells with series/parallel connections, which suffer from operating and degradation deviations. The pursuit of new, increasingly intelligent and heavier state estimation algorithms requires a significant amount of data and computational power, which can be challenging to deploy in current Battery Management System solutions. To solve this problem, this paper proposes a Digital Twin Simulation Platform that considers all the individual cells based on the Cloud to extend the computational power and data storage capacity. This work presents validated cell models, a module-level modelling approach, and an experimental validation platform is suggested. In addition, the first results obtained when implementing the Digital Twin Simulation Platform in the Cloud are presented.
... Due to limited resources of fuels, huge cost and GHE are the causes for transformation of traditional transportation to sustainable is obtained by using Electric Vehicle (EV) [3]. In EV energy storage system is playing very important role and out of many storage systems are available [4][5][6][7], battery is most reliable one. Most suitable, most reliable and more flexible to recharge the battery is nothing but the secondary battery i.e. ...
... Hence to maintain the stability during the running operation of EV, Energy storage system is ensure the tolerable values of performance parameters by maintaining the stability, reliability and optimum operation of EV. Hence by proper planning and selection of battery above mentioned parameters can be enhanced [5]. Electro mobility needs lightweight batteries which are having enough capacity to fulfil the need under fast charging and discharging mode of operation. ...
Battery-operated electric vehicles are attracting many users. Utilisations of EV are day by day increasing and hence there is need to enhance the entire performance of EV by designing the best internal parameters of the batteries used in the subsystems of EV. The performance of batteries depends on various factors, such as specific energy, life cycle, safety, internal resistances, charge and discharge time, temperature, cost, and toxicity. The main objective of this paper is to study and analyse the electric circuit model (ECM) of EV batteries to find the internal parameters by using an algorithm. The various models of ECM, such as simple model, enhanced simple model, dynamic model, Thevenin-based model, modified generic model, and Tremblay model, are critically reviewed. The Thevenin model is best suitable for simulation of battery for soc, sop etc., from predefined values of resistances and capacitor.
... Due to limited resources of fuels, huge cost and GHE are the causes for transformation of traditional transportation to sustainable by using EV (Tremblay and Dessaint, 2009). In EV ESs is playing very important role and out of many storage systems available (Shepherd, 1965;Shen et al., 2013;Miao et al., 2019;Casacca, 1992), battery is most reliable one. Most suitable, most reliable and more flexible to recharge the battery is nothing but the secondary battery, i.e., rechargeable battery. ...
... Hence to maintain the stability during the running operation of EV, ESs ensures the tolerable values of performance parameters by maintaining the stability, reliability and optimum operation of EV. Hence by proper planning and selection of battery above mentioned parameters can be enhanced (Shen et al., 2013). Electro mobility needs lightweight batteries which are having enough capacity to fulfil the need under fast charging and discharging mode of operation. ...
... Although there are other alternatives such as hydrogen storage, a battery is also required for DC bus voltage stabilization and switching on of other essential or auxiliary devices of the fuel cell system [4]. High capital costs, limited lifetime, and relatively poor performance at low temperatures are the most important issues in EVs [5][6][7][8]. Therefore, the development of efficient storage technologies is an essential part for electromobility [9]. ...
In recent decades, there has been a growing concern about the trend of global emissions, and in particular those of the transport sector. In this context, the electric vehicle is a promising technology, with some barriers still to be overcome. Among these deficiencies everything related to storage technology is found. In this sense, lithium-ion batteries are one of the options to be considered, although it is necessary to continuously monitor the state of health. Cycle life vs DoD curves are very useful for characterizing profitability in any application that considers battery storage, as well as life cycle optimization studies. Cycle life refers to the number of charge-discharge cycles that a battery can provide before performance decreases to an extent that it cannot perform the required functions (e.g., 80% compared to a fresh one in electromobility applications). In this paper, a model for calculating the Cycle Life vs DoD curves is proposed, applied to a commercially available electric vehicle, the Renault Zoe. Modelling results show R squared coefficient of determinations above 0.9890.
... Nowadays, electric vehicles are gaining in popularity due to environmental and fuel security concerns [1][2][3][4]. Lithium-ion based battery is currently an energy storage device that features properties to meet requirements for electric vehicles, specifically, high energy and power densities, high coulombic efficiency, and low cycle cost. To describe the behavior of a traction battery, a variety of battery models have been proposed in the field of research in the past decade [5][6][7][8][9][10]. ...
... Although there are other alternatives such as hydrogen storage, a battery is also required for DC bus voltage stabilization and switching on of other essential or auxiliary devices of the fuel cell system [1]. High capital costs, limited lifetime, and relatively poor performance at low temperatures are the most important issues in EVs [2][3][4][5]. Therefore, the development of efficient storage technologies is an essential part for electromobility [6]. ...
... As it can be seen in Figure 1, lithium-cobalt-oxide (LCO), nickel-cobalt-aluminum (NCA), and nickel-manganese-cobalt (NMC) technologies stand out within specific energy, but LCO can practically be discarded due to Solid Electrolyte Interphase (SEI) problems and toxicity [9]. Figure 2 shows the expected advances in specific energy for different types of battery [10]. The average lifetime of batteries in EVs tends to be approximately 8 to 10 years, which is defined by a 20%-30% degradation in battery capacity compared to its initial capacity [3]. In practice, the lifetime of a battery is reduced due to the high-power profile of the vehicle during acceleration and braking, which can be more than ten times higher than the average power. ...
... Depending on the field of study, there are several battery models, which are gathered in Table 1. The average lifetime of batteries in EVs tends to be approximately 8 to 10 years, which is defined by a 20-30% degradation in battery capacity compared to its initial capacity [3]. In practice, the lifetime of a battery is reduced due to the high-power profile of the vehicle during acceleration and braking, which can be more than ten times higher than the average power. ...
Electric vehicles (EVs) are a promising technology to reduce emissions, but its development enormously depends on the technology used in batteries. Nowadays, batteries based on lithium-ion (Li-Ion) seems to be the most suitable for traction, especially nickel-manganese-cobalt (NMC) and nickel-cobalt-aluminum (NCA). An appropriate model of these batteries is fundamental for the simulation of several processes inside an EV, such as the state of charge (SoC) estimation, capacity and power fade analysis, lifetime calculus, or for developing control and optimization strategies. There are different models in the current literature, among which the electric equivalent circuits stand out, being the most appropriate model when performing real-time simulations. However, impedance models for battery diagnosis are considered very attractive. In this context, this paper compares and contrasts the different electrical equivalent circuit models, impedance models, and runtime models for battery-based EV applications, addressing their characteristics, advantages, disadvantages, and usual applications in the field of electromobility. In this sense, this paper serves as a reference for the scientific community focused on the development of control and optimization strategies in the field of electric vehicles, since it facilitates the choice of the model that best suits the needs required.
... The reason for this may be the increase in battery temperature associated with high charge and discharge rates [6], [7]. The need for a hybrid component between a battery and a high-power device, which may lessen the demands of the battery, has been demonstrated [8], [9]. Hybrid batteries with properties of capacitors and batteries are being developed but are not yet on the market [10], [11]. ...
Hybrid vehicles are becoming increasingly popular as the world become more environmentally conscious. The efficiency of hybrid vehicles is limited by the ability of their electrochemical batteries to absorb large regenerative braking currents. Any energy over what the battery can safely absorb is dissipated through the friction brakes of the vehicle. This work will investigate the use of a dedicated high-power device, specifically an electro-mechanical flywheel, to absorb the excess energy and return it to the vehicle batteries. Both modelling and experimental approaches are utilized to analyze the increase efficiency potential, as well as the ability of the electromechanical flywheel to absorb excess braking energy. © 2019, International Journal of Electrical and Electronic Engineering & Telecommunications.
... In case 4 to case 6, an additional DC/DC converter is considered with the weight of 30kg [20]. The weight of these six powertrain systems are given in Table V. Packaging factor for UC and battery pack is assumed to be 1.2 [21]. ...
... In the problem formulation given in Eq. (21), the UC SoC is limited to 50% to 100%. As shown in the simulation results, the UC SoC is varying within a small window between 73% to 88% for this urban drive cycle. ...
In this paper, a power split control strategy is proposed for an electric vehicle (EV) powertrain with two propulsion machines and a battery/ultra-capacitor (UC) hybrid energy storage system (HESS). The proposed power split control strategy consists of two stages. In the first stage, the load power is split between the two propulsion machines to obtain the highest powertrain efficiency in both propulsion and regenerative braking modes. A real-time implementable power split control strategy is proposed to benefit from complementary operation features of these two propulsion machines. In the second stage, the load power is split between the battery pack and UC in the HESS. To optimize the power split in HESS, a convex optimization problem is formulated to minimize the battery power magnitude and battery current variations to extend the battery lifetime. The implementation of proposed power split control strategy in the powertrain of an EV with two propulsion machines will potentially result in up to 10% improvement in the powertrain efficiency and up to 82% extension of the battery lifetime. The improvement of propulsion efficiency will in turn lead to up to 27% extension of all-electric driving range.
... As shown in Fig. 4, with the proposed control strategy implemented in the battery/UC HESS, the battery power magnitude is reduced by 58.44% in comparison to the batteryonly ESS. In order to estimate the battery lifetime extension, a battery degradation model given in [12] is utilized. In this model, the temperature, the depth-of-discharge (DOD) and the C-rate effects on capacity loss are considered. ...
In this paper, a power split control strategy is proposed for an electric vehicle (EV) powertrain with two propulsion machines and a battery/ultra-capacitor (UC) hybrid energy storage system (HESS). Using this supervisory control strategy, the load power is effectively split between the two propulsion machines to obtain the highest powertrain efficiency in both propulsion and regenerative braking modes. In addition, in order to optimize the power split in HESS, a convex optimization problem is formulated to minimize the battery power magnitude and battery current variations. With the proposed supervisory control strategy, 10% improvement in the powertrain efficiency and 82% extension of the battery lifetime is expected.
