The performance of on-board power batteries in electric vehicles directly affects the vehicle's driving range. The safety of on-board lithium-ion battery packs and the uneven charging issues caused by series chargers are major obstacles to their development. Based on the development status of electric vehicle power batteries both domestically and internationally, this paper focuses on introducing the structure and core functions of lithium-ion battery management systems, which show promising prospects.
Electric vehicles, which use electricity to replace fossil fuels as their power source, represent the only long-term solution for future transportation. As the heart of electric vehicles, the power battery system requires a thorough understanding to ensure the successful adoption of electric vehicles. This article focuses on analyzing the promising lithium-ion batteries and their battery management systems, examining the development trends of major on-board power batteries for electric vehicles both domestically and internationally.
Uneven charging by lithium-ion battery chargers can easily lead to overcharging and over-discharging problems, severely damaging the battery's lifespan. This paper proposes a novel intelligent charger charging mode that enables safer and more reliable charging of battery packs, extending their lifespan, increasing safety, and reducing operating costs.
1. Vehicle-mounted lithium-ion battery management system
As the monitoring "brain" of electric vehicle batteries, the Battery Management System (BMS) in hybrid electric vehicles can monitor the remaining battery charge, predict the battery's power intensity, and facilitate understanding of the entire battery system and control of the whole vehicle system.
In pure electric vehicles, Battery Management Systems (BMS) possess intelligent adjustment functions such as predicting remaining battery power, predicting driving range, and fault diagnosis. The role of BMS is particularly significant for lithium-ion batteries, improving battery performance, extending battery life, and increasing battery safety. BMS will be a key technology for the future development of electric vehicles.
As shown in Figure 1, the data acquisition module in the BMS measures the voltage, current, and temperature of the battery pack, and then transmits the collected data to the thermal management module and the safety management module for display. The thermal management module controls the temperature of individual battery cells to ensure that the battery pack is within its optimal temperature range.
The safety management module assesses the battery pack's voltage, current, temperature, and state of charge (SOC) estimation results. When a fault occurs, it issues a fault alarm and promptly implements emergency protection measures such as circuit breaking. The state estimation module estimates SOC and state of health (SOH) based on the collected battery state data.
Currently, SOC estimation is the primary method, while SOH estimation technology is still immature. The energy management module controls the battery's charging and discharging process, including battery power balancing management to eliminate inconsistencies in the charge levels of individual cells within the battery pack. The data communication module uses CAN communication to enable communication between the BMS and on-board and off-board equipment.
The core functions of a Battery Management System (BMS) are SOC estimation, equalization management, and thermal management. It also includes other functions such as charge/discharge management and pre-charger charging management. During battery charging and discharging, management is required based on environmental conditions, battery status, and other relevant parameters to set the optimal charge/discharge curve for the battery. This includes setting the charger charging current, the upper limit voltage for charging, and the lower limit voltage for discharging. The capacitive load in the high-voltage system circuit of an electric vehicle is equivalent to a short circuit at the moment of power-on; therefore, pre-charger charging management is necessary to prevent transient current surges in the high-voltage circuit.
2. Core Functions of the Battery Management System
2.1 SOC Estimation
State of Charge (SOC) describes the remaining charge of a battery and is one of the most important parameters during battery use. SOC estimation is the basis for judging overcharge and over-discharge of a battery. Accurate estimation can minimize the problem of overcharging and over-discharging of the battery pack, making it operate more reliably.
The estimation of battery SOC exhibits a highly nonlinear nature under the influence of changes in internal operating environment and external usage environment. Many internal and external factors affect battery capacity, such as battery temperature, battery life, and battery internal resistance, making accurate SOC estimation very difficult.
The existing SOC estimation methods are as follows:
(1) Ampere-hour measurement method. The ampere-hour measurement method does not consider changes in the internal structure and state of the battery, thus it has the advantages of simple structure and convenient operation. However, the accuracy of this method is not high. If the current measurement accuracy is not high, the cumulative error of SOC will continue to increase over time, affecting the final result. This method is suitable for measuring the SOC of batteries in electric vehicles. If the measurement accuracy can be improved, it is a simple and reliable SOC measurement method.
(2) Open-circuit voltage method. The open-circuit voltage of a lithium-ion battery has an approximately linear relationship with its state of charge (SOC), which can be used to determine the internal state of the battery. However, due to the stringent measurement requirements, the battery needs to be left to stand for at least 1 hour, making it unsuitable for online real-time monitoring of batteries in electric vehicles. Generally, because the open-circuit voltage method has a high accuracy rate in estimating values at the beginning and end of charging, it is often used in combination with the ampere-hour metering method.
(3) Kalman filtering method. The Kalman filtering method is particularly suitable for hybrid batteries with drastic current fluctuations due to its excellent error correction capability. The disadvantage of this estimation method is that it requires a high system processing speed.
(4) Neural Network Method. Neural networks have characteristics such as distributed parallel processing, nonlinear mapping, and adaptive learning, so they can be used to simulate battery dynamic characteristics and estimate SOC. However, this method requires a large amount of reference data for the neural network to learn from, and the data and training methods are highly demanding; otherwise, unacceptable errors will occur.
2.2 Balanced Management
The battery manufacturing process involves many steps, and variations can lead to inconsistencies. The differences between individual battery cells are mainly reflected in their internal resistance and capacity, which change over time and with temperature variations. Large differences between cells are more likely to cause overcharging or over-discharging, resulting in battery damage. Achieving battery balancing maximizes the effectiveness of the power battery, extends its lifespan, and increases safety. Currently, the mainstream balancing methods both domestically and internationally are as follows:
(1) Resistance balancing method. This method is the main representative of energy dissipation balancing method. It is simple and low cost, but the energy loss is relatively large and the efficiency is low. It is only suitable for systems with small current charging and discharging.
(2) Switched capacitor method. This method is the main representative of non-energy dissipation equalization method, which makes up for the shortcomings of resistance equalization. However, its control circuit is complex, the equalization speed is slow, and the time is long, making it unsuitable for high current applications.
(3) Transformer balancing method. This method is an active balancing control method for series battery packs based on a symmetrical multi-winding transformer structure. Its disadvantages are complex circuitry, numerous components, large size, and difficulty in expanding the battery pack. It is generally suitable for high-current charging and discharging.
(4) Centralized equalization. This method can quickly transfer energy from the entire battery pack to individual battery cells, and the centralized equalization module is smaller. However, equalization operations for multiple batteries cannot be performed in parallel, and a large number of cables are required, making it unsuitable for battery packs with a large number of batteries.
2.3 Heat Management
Temperature affects all aspects of battery performance. Inhomogeneity in the temperature field exacerbates inconsistencies within the battery pack, making its management essential. The purpose of thermal management is to maintain the battery system temperature within a certain range and, as far as possible, ensure temperature uniformity within the battery pack through heating or cooling measures.
Temperature management mainly performs the following four functions: (1) rapidly heating the battery pack under low resistance conditions; (2) ensuring a uniform distribution of the battery temperature field; (3) accurately measuring and monitoring the battery temperature; and (4) effectively dissipating heat when the battery pack temperature is too high. Commonly used cooling methods include natural convection, forced air convection, liquid flow, phase change material methods, and thermal management methods. Commonly used heating methods include internal battery heating, heating plate methods, heating jacket methods, and heat pump methods.
3. Lithium-ion battery charger charging technology
3.1 Current Status and Development Trends
In practical applications, selecting different charger charging modes based on battery capacity limitations is essential for extending battery life. There are various charging methods for lithium-ion batteries, the simplest being the constant voltage charger method. Lithium-ion battery packs are generally composed of a large number of cells connected in series . Due to differences in the manufacturing process of each cell, inconsistencies exist in internal resistance, voltage, capacity, and temperature, easily leading to imbalances during charging and discharging—large-capacity cells are shallowly discharged while small-capacity cells are over-discharged. This can severely damage the battery pack. Solving the problem of uneven charging and discharging is a key research focus for lithium-ion battery packs.
The requirements for battery charger technology in electric vehicles include:
(1) Faster charging process. The low specific energy of power batteries results in a short driving range on a single charge, which has always been a major factor limiting the development of electric vehicles. By enabling faster and more efficient charging of batteries, this major weakness of short driving range of electric vehicles can be indirectly compensated for.
(2) Standardization of charging equipment. In order to pursue the forefront of relevant academic research, optimize their own products, and strive for the largest possible market share, various new types of batteries are emerging and coexisting in this market. With the coexistence of different types and voltage levels of batteries, charging equipment in public places needs to have a wider range of adaptability. On the one hand, the charging equipment needs to be compatible with as many batteries as possible; on the other hand, for different voltage levels, the charging equipment needs to meet the requirements of customers.
(3) Intelligent charging strategy of the charger. In order to achieve lossless charging of the battery as much as possible, monitor its charging and discharging status, avoid over-discharge, and achieve the goal of saving energy and delaying aging, a more intelligent charging strategy is needed. That is, to provide different charging strategies for different batteries to match the charging curve of the battery.
(4) Improve the efficiency of power conversion. The energy loss of electric vehicles is closely related to their operating costs. In order to further promote electric vehicles, it is necessary to balance their cost-effectiveness as much as possible and reduce energy consumption.
(5) Integration of charger charging system. With the increasing demands for system miniaturization and multifunctionality, as well as the increasing requirements for battery reliability and stability, the charger charging system will be integrated with the electric vehicle energy management system into a whole, integrating functions such as current detection and reverse discharge protection. This will enable a smaller and more integrated charger charging solution without the need for external components, thereby saving space for the other components of the electric vehicle, greatly reducing system costs, optimizing charger charging performance, and extending battery life.
3.2 Smart charger charging technology
Based on the above analysis of the current charging status of lithium-ion battery packs and their chargers, and in response to the imbalance and safety issues that are prone to occur during the charging process of lithium-ion battery pack chargers, this paper summarizes a smart charger charging mode based on electric vehicle BMS, as shown in Figure 2.
Throughout the charging process, the BMS system primarily monitors the battery voltage and current signals, as well as temperature and connection status of the lithium-ion battery pack. The intelligent management system within the charger monitors the output mode of the charging equipment in real time. The BMS system and the intelligent management system of the charging equipment communicate intelligently, comparing the real-time status of the battery pack and the charging equipment to select the optimal charging mode for the battery pack.
During the initial charging process, the BMS estimates the maximum allowable charging capacity of the lithium-ion battery pack. This involves evaluating the State of Charge (SOC) of each individual cell in the entire battery pack to determine the maximum rechargeable capacity of the pack. Combined with a pre-set charging capacity safety factor, the maximum permissible charging capacity of the battery pack is calculated.
During the charging process, the lithium-ion battery pack is charged according to the maximum allowable charging capacity. The energy management module of the BMS is fully utilized to perform charging equalization control on the individual battery cells, ensuring consistency of individual cell parameters. Simultaneously, the SOC value needs to be periodically monitored during charging (the monitoring cycle is determined based on the gradient of battery charge increase).
By utilizing the state estimation function of the BMS system and combining it with safety management, overcharging of the battery pack can be prevented to the greatest extent possible. Once the maximum charging capacity of the battery pack is reached, both the BMS and the intelligent management system for the charging equipment can intelligently control the charging controller to terminate the charging process. Simultaneously, the BMS disconnects communication with the intelligent monitoring system for the charging equipment.
The intelligent charger not only solves the problem of uneven charging in lithium-ion battery packs, but also maximizes the charging safety of the battery packs, extends the lifespan of lithium-ion batteries, and ensures their safe use.
4. Lithium-ion battery testing technology
my country is vigorously developing the electric vehicle industry and actively promoting the construction of related charging infrastructure. However, many problems have been discovered in the operation of these demonstration devices, such as battery selection and matching, equipment overheating, and poor contact at the plug-in interfaces of the connecting devices. If these problems, which have appeared in a small number of devices, cannot be resolved, a situation of being overwhelmed will arise after the large-scale application of electric vehicles, which will inevitably have an adverse impact on its development.
With the large-scale construction of electric vehicle infrastructure, there is an urgent need for related testing solutions. Tianjin Electric Power Company launched the "Research on Testing Technology of Key Charging Equipment for Mobile Electric Vehicle Chargers" project, among which the most important aspect for electric vehicle battery swapping stations is the testing of battery packs.
Electric vehicle battery swapping stations primarily include battery fault diagnosis, screening and maintenance, and battery management system (BMS)-based charging technology using individual charging units. The performance of both the battery screening device and the charging unit will be the focus of testing. Research and understanding of the characteristics of lithium-ion batteries will help determine the accuracy of the screening devices in the swapping station and improve battery lifespan.
By conducting research on a large number of operational chargers and key charging equipment, we can better understand their operational and fault characteristics, improve testing efficiency, and develop a simple and efficient mobile testing solution. This will provide a strong core technological guarantee and contribute to the comprehensive development of electric vehicles.
5 Conclusion
This paper analyzes lithium-ion battery systems, focusing on the composition and core functions of the Battery Management System (BMS). It proposes an intelligent charger charging mode to address the issue of uneven charging between the battery pack and the charger. A complete intelligent charger charging system can coordinate the supply and demand relationship between the charger and the battery pack, providing a safer and more reliable charging mode for the battery pack, extending its lifespan, increasing battery pack reliability, and reducing operating costs. This will become a key research focus in future electric vehicle technology. Therefore, the development of convenient and rapid "mobile" charger testing devices to match intelligent charger charging technology is imperative.
