Charging control of lithium‐ion battery and energy management system in electric vehicles

Intelligent algorithms and control strategies for battery management system in electric vehicles: Progress, challenges and future outlook

Electric vehicles are playing a very important role in saving Non-renewable energy sources as they are limited. Battery electric vehicles are precious as compared to combustion engines because of their efficiency and they don't emit exhaust gasses that are harmful to the ecosystem. Electric vehicles use electric motors instead of a combustion engine which have battery packs as an energy source. Battery packs consist of a huge amount of cells. The large number of cells that are initially different in voltage makes it difficult to manage. The difference in initial voltage of cells damages the battery pack and if the battery pack gets damaged, then the electric vehicle is of no use. A Battery Management System (BMS) is an electronic system that controls the charging and discharging of a rechargeable battery cell or battery pack, for example, by protecting the cell or the battery pack from operating outside of its safe operating range, managing its condition, reporting data, controlling its conditions, authenticating it, and/or balancing it. The bidirectional functionality of the BMS provides consistent battery capacity and draining of all Lithium-ion battery cells. A digital voltmeter and ammeter are used for switching the solid-state switch which is a MOSFET-based switch. The constant voltage and constant current source are used to protect the battery cells from any kind of internal damage.

Battery electric vehicles (BEVs) have been widely publicized. Their driving performances depend mainly on lithium-ion batteries (LIBs). Research on this topic has been concerned with the battery pack’s integrative environmental burden based on battery components, functional unit settings during the production phase, and different electricity grids during the use phase. We adopt a synthetic index to evaluate the sustainability of battery packs. A life cycle assessment (LCA) is used to reveal the aspects of global warming potential (GWP), water consumption, and ecological impact during the two phases. An integrative indicator, the footprint-friendly negative index (FFNI), is combined with footprint family indicators of battery packs and electricity sources. We investigate two cases of 1 kg battery production and 1 kWh battery production to assess nickel–cobalt–manganese (NMC) and lithium–iron phosphate (LFP) battery packs and compare their degrees of environmental friendliness. Then, we break down the battery pack to identify the key factors influencing the environmental burden and use sensitivity analysis to analyze the causes. Moreover, we evaluate the environmental impact of battery packs during the use phase among different regions. Regardless of the functional unit (FU), the weights of the carbon footprint (CF), water footprint (WF), and ecological footprint (EF) are approximately the same. The results of the integrative environmental indicator, the FFNI, illustrate that the LFP is approximately 0.014, which is lower than that of the NMC battery pack in the mass production case. When using energy units as the FU, the FFNI of the NMC is 0.015, which reflects a lower environmental burden than that of other battery packs. In the use phase, 1kWh electricity consumption in China and Europe has the highest and lowest FFNI, respectively. When breaking down the battery-pack components, the simplified model advocates the cathode as the major contributor that determines the total environmental performance. In the following sensitivity analysis, the battery management system (BMS) is found to be the most intensive part of the footprint of most battery packs. FU can influence the evaluation results. Developing proper renewable energy sources can reduce the footprints of battery packs during the use phase. The positive electrode pastes in the battery cell, BMS, and packaging in the battery pack can influence the environmental burden. Adopting green materials in sections like the BMS may be a specific measure to enhance the environmental friendliness of a battery pack during the production phase.

In this paper, a 12-bit incremental sigma-delta (ΣΔ) analog to digital converter (ADC) for the lithium battery management system (BMS) in electric vehicles is presented. In order to reduce the power consumption and the required clock cycles in one conversion, a second order incremental ΣΔ architecture with single feedback loop is adopted for the modulator of the ADC. The ADC is designed with a 0.5µm BCD process under a power supply voltage of 5V and a sampling clock frequency of 1MHz. Measurement results show that only 512 clock cycles is required for the conversion of one battery voltage, with a maximum absolute conversion error of less than 3mV. The power consumption is less than 510mA and the chip area of the ADC is 500×800µm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

Energy efficient machine learning based SMART-A-BLE implemented Wireless Battery Management System for both Hybrid Electric Vehicles and Battery Electric Vehicles

Input voltage, current, and temperature measurement circuits are the vital concerns of a Battery Management System (BMS) in electric vehicles. There are several approaches proposed to analyze the parameters of voltage, current, and temperature of a battery. This paper proposes a BMS methodology that is designed using linear optocouplers. In this paper, the optocouplers are incorporated between the battery pack and the BMS, which can be used in automotive applications for accurate measurements. The functions of BMS, such as measuring the current, voltage, and temperature in real time, can be executed using the proposed methodology.

Advances in battery state estimation of battery management system in electric vehicles

The networking requirement in CPS and IOT systems increase the performance in the involved application, but also introduce security vulnerabilities to the system. The increased power capacity and networking requirements in Fast and Extremely Fast Charging (XFC) systems for battery electric vehicles (BEVs) and the resulting increase in the adversarial attack surface sets a good example for such threats and call for security measures to be taken in the involved cyber-physical system (CPS) as a whole. This study proposes a moving-target defense (MTD) based novel approach for the battery management system (BMS) of an electric vehicle during the charging process, focusing specifically on spoofing and replay attacks to the CAN bus, which could contaminate the whole grid through the BMS. To our best knowledge, this is one of the first studies in the literature on security-hardened BMS and charging process, aiming to increase the security of operations between the charging station, batteries and BMS of electric vehicles. The performed simulations for a BMS redundancy of four demonstrate increased security and optimized charging performance under adversarial attacks to the CAN bus and without the overhead of authentication methods in the literature. The developed MTD strategies can also support intrusion detection schemes, and could be extended to other CPS and IOT systems with security concerns.

Applications of artificial intelligence and cell balancing techniques for battery management system (BMS) in electric vehicles: A comprehensive review

The Battery management system (BMS) is a main component in the battery pack system for electric vehicles (EV). The function of BMS is to monitor battery cells such as; cell voltage, cell temperature, and current in the battery pack. Moreover BMS also able to balance the voltage of the cells so the difference in voltage of the cells can be minimized. By having many of these functions, BMS can identify battery health based on these parameters. With such an important function, in this paper, BMS was tested to determine its reliability. The standard testing for BMS reliability is the Environment test. In the environment test, some things that are conducted in the environment test are initial temperature cycling. From the environment, the test can be generated information to assess the quality of the BMS following its function. Furthermore, it can reduce the cost to inspect every battery cells in the packs. With the environment test as a basis for BMS reliability tester, hopefully, good quality is obtained. Future development in BMS reliability testing can also be conducted to improve reliability.

As the bridge of battery and vehicle management system and the drivers, battery management system (BMS) for electric vehicle performance is playing a more and more key role. This article introduces several kinds of battery display methods and displays, and for each display method on the feasibility study, also focuses on the electric car batteries systematic, modular design and the chip integration technology of battery management system.

Electric vehicles (EVs) are the fastest-growing type of transport. Battery packs are a key component in EVs. Modern lithium-ion battery cells are characterized by low self-discharge current, high power density, and durability. At the same time, the battery management system (BMS) plays a pivotal role in ensuring high efficiency and durability of battery cells and packs. The BMS monitors and controls the battery charge and discharge to ensure EV safety and optimum operation. This paper is devoted to analyzing BMS circuitry configurations and algorithms. The analysis includes circuit solutions and algorithms for implementing the main BMS functions, such as parameter monitoring, protection, cell balancing, state estimation, charging and discharging management, communication, and data logging. The paper provides insights into the recent research literature on BMS, and the advantages and disadvantages of methods for implementing BMS functions are compared. The paper also discusses the application of artificial intelligence technologies and aspects of further work on next-generation BMS technologies.

Battery and energy management system for vanadium redox flow battery: A critical review and recommendations

Development of prototype battery management system for PV system

Battery packs comprising of assembly of batteries also known as the battery management system is considered as heart of the electric vehicle system. The present work will conduct the detailed survey on the two aspects of battery management systems such as the control by battery modelling and Mechanical designs. The findings reported that a considerable and significant research in battery modelling for estimating the battery states based on the empirical, semi-empirical, electrical, thermal, fusion and electrochemical models had been conducted. Relatively, the research on the mechanical designs for the battery management system has been overlooked. This work provides an overview of the present research focus, the critical gaps with the new research directions, which can also be seen as an outlook, challenges and opportunities in designing of an efficient battery management systems for the next-generation electric vehicles. The critical directions of research identified are a) Uncertainty in the battery estimation b) Mechanical design of robust battery pack c) Emerging battery technologies d) Sustainable and manufacturable battery pack e) Unified and Conceptual model f) Safe location for easy installation and replacement of the battery pack. Future work for authors would be to work on these research directions and innovate a compact mechanical design of a battery pack that is reliable, endurable, sustainable and economically viable.