Modeling and Simulation of Working Characteristics of Lithium Titanate Batteries for Emergency Power Transmission

This paper presents a battery model applied to dynamic simulation software. The simulation model uses only the battery State-Of-Charge (SOC) as a state variable in order to avoid the algebraic loop problem. It is shown that this model, composed of a controlled voltage source in series with a resistance, can accurately describe the lithium titanate battery discharge process. The model’s parameters can be easily extracted from the manufacturer’s discharge curve. In this paper, it is actually applied to the self-starting system after the emergency stop of the EMU, the simulation model of the system is established by MATLAB/Simulink, and the ground test platform is used to simulate the actual working condition of EMU to complete the experimental verification. The results of both simulation and experiment proved that the scheme of battery self-shifting driven system is feasible and correct

Experimental evaluation of a passive fuel cell/ battery hybrid power system for an unmanned ground vehicle

Unmanned vehicles are increasing the performance of monitoring and surveillance in several applications. Endurance is a key issue in these systems, in particular in electric vehicles, powered at present mainly by batteries. Hybrid power systems based on batteries and fuel cells have the potential to achieve high energy density and specific energy, increasing also the life time and safe operating conditions of the power system. The objective of this research is to analyze the performance of a passive hybrid power system, designed and developed to be integrated into an existing Unmanned Ground Vehicle (UGV). The proposed solution is based on six LiPo cells, connected in series, and a 200 W PEM fuel cell stack, directly connected in parallel to the battery without any limitation to its charge. The paper presents the characterization of the system behavior, and shows the main results in terms of performance and energy management.The authors would like to acknowledge the NATO Science for Peace and Security Program for partially funding this work through the project “Improving efficiency and operational range in low-power unmanned vehicles through the use of hybrid fuel-cell power systems” (IUFCV), Ref. 985079

Design Methodology for the Electrification of Urban Bus Lines with Battery Electric Buses

Electrically powered buses reduce CO$_{2}$ and noise emissions in urban areas and thus promote the trend towards more livable cities. Upon this reason, more and more cities are introducing their first electrified lines as pilot projects. However, no standardized technology has yet emerged, which is why statements on interactions between vehicle, operation and infrastructure in public transport are proving to be difficult to make. In order to be able to make statistically significant statements in this respect, a simulation model was developed that depicts the three subsystems vehicle, operation and infrastructure. On the basis of measurement data from the PRIMOVE research project in Mannheim, in which an urban bus line is operated with two electrically powered buses, the simulation model was validated and a data basis was laid for further investigations. As a result, simulation studies with more than 700 simulated operating days could be carried out, the results of which represent the input for the following statistical analysis. Based on this analysis, the interactions described above will be demonstrated in the design of the main technical parameters, the battery lifespan and the energy demand of electrical bus lines. Through the findings of these simulations, an optimized version of the already electrified bus line in Mannheim will then be presented. Finally, a novel design methodology for electrification based on a multi-objective optimization is introduced. All parameters of the system are variable in order to apply the presented methodology to other projects and thus underline the general validity of the work

MatLab simulation model for dynamic mode of the Lithium-Ion batteries to power the EV

The paper presents a simulation model for the electric vehicles (EV) drive with Lithium-Ion batteries. Explanations of all the input parameters are given. Analysis of the dynamic characteristics of Lithium-Ion batteries was carried out through simulations on standardized driving regime (urban and highway drive cycles). Finally, recuperation of breaking energy of EV is explained

Performance analysis of batteries used in electric and hybrid electric vehicles

Hybrid electric vehicles (HEVs) and electric vehicles (EVs) are the most viable solutions to the undesirable high petroleum consumption by the present form of internal combustion engine driven vehicles. The varying requisites of HEVs and EVs have resulted in the advancement of battery technology in the area of chemical compositions such as electrode and electrolyte in addition to its electrical combination, control and protection schemes. The maximum utilization and protection of the battery is a challenge that needs to be tackled to improve its efficiency and reliability. A comprehensive study of the present battery technology has been performed in this thesis. The research is focused on battery modeling and its applications taking the complete electric drive train into consideration. Novel models and research perspectives have been proposed and analyzed. The scopes of increasing the accuracy of the present day battery management system have also been discussed

On the possibility of extending the lifetime of lithium-ion batteries through optimal V2G facilitated by a flexible integrated vehicle and smart-grid system

Renewable energies are a key pillar of power sector decarbonisation. Due to the variability and uncertainty they add however, there is an increased need for energy storage. This adds additional infrastructure costs to a degree that is unviable: for an optimal case of 15GW of storage by 2030, the cost of storage is circa: £1000/kW. A promising solution to this problem is to use the batteries contained within electric vehicles (EVs) equipped with bi-directional charging systems to facilitate ancillary services such as frequency regulation and load balancing through vehicle to grid (V2G) technologies. Some authors have however dismissed V2G as economically unviable claiming the cost of battery degradation is larger than arbitrage. To thoroughly address the viability of V2G technologies, in this work we develop a comprehensive battery degradation model based on long-term ageing data collected from more than fifty long-term degradation experiments on commercial C6/LiNiCoAlO2 batteries. The comprehensive model accounts for all established modes of degradation including calendar age, capacity throughput, temperature, state of charge, depth of discharge and current rate. The model is validated using six operationally diverse real-world usage cycles and shows an average maximum transient error of 4.6% in capacity loss estimates and 5.1% in resistance rise estimates for over a year of cycling. This validated, comprehensive battery ageing model has been integrated into a smart grid algorithm that is designed to minimise battery degradation. We show that an EV connected to this smart-grid system can accommodate the demand of the power network with an increased share of clean renewable energy, but more profoundly that the smart grid is able to extend the life of the EV battery beyond the case in which there is no V2G. Extensive simulation results indicate that if a daily drive cycle consumes between 21% and 38% state of charge, then discharging 40% to 8% of the batteries state of charge to the grid can reduce capacity fade by approximately 6% and power fade by 3% over a three month period. The smart-grid optimisation was used to investigate a case study of the electricity demand for a representative University office building. Results suggest that the smart-grid formulation is able to reduce the EVs’ battery pack capacity fade by up to 9.1% and power fade by up to 12.1%

Advances in Batteries, Battery Modeling, Battery Management System, Battery Thermal Management, SOC, SOH, and Charge/Discharge Characteristics in EV Applications

The second-generation hybrid and Electric Vehicles are currently leading the paradigm shift in the automobile industry, replacing conventional diesel and gasoline-powered vehicles. The Battery Management System is crucial in these electric vehicles and also essential for renewable energy storage systems. This review paper focuses on batteries and addresses concerns, difficulties, and solutions associated with them. It explores key technologies of Battery Management System, including battery modeling, state estimation, and battery charging. A thorough analysis of numerous battery models, including electric, thermal, and electro-thermal models, is provided in the article. Additionally, it surveys battery state estimations for a charge and health. Furthermore, the different battery charging approaches and optimization methods are discussed. The Battery Management System performs a wide range of tasks, including as monitoring voltage and current, estimating charge and discharge, equalizing and protecting the battery, managing temperature conditions, and managing battery data. It also looks at various cell balancing circuit types, current and voltage stressors, control reliability, power loss, efficiency, as well as their advantages and disadvantages. The paper also discusses research gaps in battery management systems.publishedVersio