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Lithium ion batteries used in electric vehicles have large capacity, multiple series and parallel connections, complex systems, and high performance requirements for safety, durability, and power, making it difficult to achieve. Therefore, they have become a bottleneck affecting the promotion and popularization of electric vehicles. The safe working area of lithium-ion batteries is limited by temperature and voltage windows. Beyond this window range, battery performance will accelerate and even cause safety issues. At present, most lithium-ion batteries used in vehicles require a reliable operating temperature of -20~55C during discharge and 0~45C during charging (for graphite negative electrodes), while the minimum temperature for LTO charging with negative electrodes is -30C; The working voltage is generally around 1.5-4.2V (about 2.5-4.2V for LiCoO2/C, LiNi0.8Co0.15Al0.05O2/C, LiCoxNiyMnzO2/C, and LiMn2O4/C material systems, about 1.5-2.7V for LiMn2O4/Li4Ti5O12 material systems, and about 2.0-3.7V for LiFePO4/C material systems).

Temperature has a decisive impact on the performance, especially the safety, of lithium-ion batteries. Depending on the type of electrode material, the typical operating temperature of lithium-ion batteries (C/LiMn2O4, C/LMO, C/LiCoxNiyMnzO2, C/NCM, C/LiFePO4, C/LiNi0.8Co0.15Al0.05O2, C/NCA) is as follows: discharge at -20-55 ℃, charge at 0-45 ℃; When the negative electrode material is Li4Ti5O12 or LTO, the minimum charging temperature can often reach -30 ℃.

When the temperature is too high, it can have a negative impact on the battery's lifespan. When the temperature reaches a certain level, it may cause safety issues. As shown in Figure 1, when the temperature is between 90 and 120 ℃, the SEI film will begin to undergo exothermic decomposition [1-3], while some electrolyte systems will decompose at lower temperatures of about 69 ℃ [4]. When the temperature exceeds 120 ℃, the SEI film decomposes and cannot protect the negative carbon electrode, causing the negative electrode to react directly with the organic electrolyte, resulting in combustible gas. When the temperature is 130 ℃, the separator will begin to melt and close the ion channel, causing the positive and negative poles of the battery to temporarily have no current flow [5,6]. As the temperature increases, the positive electrode material begins to decompose (LiCoO2 begins to decompose at about 150 ℃ [7], LiNi0.8Co0.15Al0.05O2 at about 160 ℃ [8,9], LiNixCoyMnzO2 at about 210 ℃ [8], LiMn2O4 at about 265 ℃ [1], LiFePO4 at about 310 ℃ [7]) and oxygen appears. When the temperature exceeds 200 ℃, the electrolyte will decompose and produce flammable gases [3], and react violently with the oxygen generated by the decomposition of the positive electrode [9], leading to thermal runaway. Charging below 0 ℃ will cause lithium metal to form an electroplating layer on the negative electrode surface, which will reduce the cycling life of the battery. [10]

Low voltage or over discharge can cause the electrolyte to decompose and produce combustible gases, leading to potential safety risks. Excessive voltage or overcharging may cause the positive electrode material to lose activity and generate a large amount of heat; Ordinary electrolytes decompose when the voltage exceeds 4.5V

In order to solve these problems, people are trying to develop new battery systems that can operate in very harsh conditions. On the other hand, currently commercialized lithium-ion batteries must be connected to a management system, so that lithium-ion batteries can be effectively controlled and managed. Each single battery operates under appropriate conditions, fully ensuring the safety, durability, and power performance of the battery.

2. Meaning of battery management system

The important task of a battery management system is to ensure the design performance of the battery system, which can be decomposed into the following three aspects:

1) Safety, protecting battery cells or battery packs from damage and preventing safety accidents;

2) Durability, allowing the battery to operate in a reliable and safe area, extending its service life;

3) Power performance, maintaining battery operation in a state that meets vehicle requirements. The safe working area of lithium-ion batteries is shown in Figure 1.

BMS is composed of various sensors, actuators, controllers, and signal wires. To meet relevant standards or specifications, BMS should have the following functions.

1) Battery parameter detection. This includes detection of total voltage, total current, individual battery voltage (to prevent overcharging, discharging, or even reverse polarity), temperature detection (preferably with temperature sensors for each string of batteries, key cable joints, etc.), smoke detection (to monitor electrolyte leakage, etc.), insulation detection (to monitor leakage), collision detection, etc.

2) Battery state estimation. This includes State of Charge (SOC) or Depth of Discharge (DOD), State of Health (SOH), Functional State (SOF), Energy State (SOE), Fault and Safety State (SOS), etc.

3) Online fault diagnosis. Including fault detection, fault type judgment, fault location, fault information output, etc. Fault detection refers to the use of diagnostic algorithms to diagnose fault types and provide early warning based on collected sensor signals. Battery failure refers to sensor failures, actuator failures (such as contactors, fans, pumps, heaters, etc.), network failures, and various controller software and hardware failures in subsystems such as battery packs, high-voltage power circuits, and thermal management. The fault of the battery pack itself refers to overvoltage (overcharging), undervoltage (overdischarge), overcurrent, ultra-high temperature, internal short circuit fault, loose connector, electrolyte leakage, insulation reduction, etc.

4) Battery safety control and alarm. Including thermal system control and high-voltage electrical safety control. After BMS diagnoses a fault, it notifies the vehicle controller through the network and requires the vehicle controller to take effective measures (BMS can also cut off the main circuit power supply when exceeding a certain threshold) to prevent damage to the battery and personnel caused by high temperature, low temperature, overcharging, discharging, overcurrent, leakage, etc.

5) Charging control. BMS has a charging management module that can control the charger to safely charge the battery based on its characteristics, temperature, and power level.

6) Battery balancing. The existence of inconsistency results in the capacity of the battery pack being smaller than the capacity of the smallest individual in the group. Battery balancing refers to the use of active or passive, dissipative or non dissipative balancing methods based on individual battery information, in order to make the battery pack capacity as close as possible to the minimum individual capacity.

7) Thermal management. According to the temperature distribution information in the battery pack and the charging and discharging requirements, determine the intensity of active heating/cooling, so that the battery can work at the most suitable temperature as far as possible, and give full play to the performance of the battery.

8) Network communication. BMS needs to communicate with network nodes such as the vehicle controller; At the same time, it is not convenient to disassemble the BMS on the vehicle, which requires online calibration, monitoring, automatic code generation, and online program download (program updates without disassembling the product) without disassembling the shell. Generally, the vehicle network adopts CAN bus technology.

9) Information storage. Used to store key data such as SOC, SOH, SOF, SOE, cumulative charge discharge Ah, fault codes, and consistency. The actual BMS in the vehicle may only have some of the hardware and software mentioned above. Each battery unit should have at least one battery voltage sensor and one temperature sensor. Regarding a battery system with dozens of batteries, there may only be one BMS controller, or even BMS functionality integrated into the vehicle's main controller. For a battery system with hundreds of battery cells, there may be one main controller and multiple slave controllers that only manage one battery module. Regarding each battery module with dozens of battery cells, there may be some module circuit contactors and balance modules, and the controller manages the battery module, controls the contactors, balances the battery cells, and communicates with the main controller like measuring voltage and current. Based on the reported data, the main controller will perform battery status estimation, fault diagnosis, thermal management, etc.

10) Electromagnetic compatibility. Due to the harsh operating environment of electric vehicles, it is required that the BMS has good electromagnetic interference resistance and low external radiation. The basic framework of electric vehicle BMS software and hardware is shown in Figure 2.

3. Key issues with BMS

Although BMS has many functional modules, this article only analyzes and summarizes its key issues. At present, key issues involve battery voltage measurement, data sampling frequency synchronization, battery state estimation, battery uniformity and balance, and accurate measurement of battery fault diagnosis.

3.1 Battery voltage measurement (CVM)

The difficulties in measuring battery voltage lie in the following aspects:

(1) The battery pack of an electric vehicle has hundreds of battery cells connected in series, requiring many channels to measure voltage. Due to the accumulated potential of the measured battery voltage, which varies for each battery, it is impossible to eliminate errors using one-way compensation methods.

(2) High accuracy is required for voltage measurement, especially for C/LiFePO4 batteries. SOC estimation places high demands on battery voltage accuracy. Here we take C/LFP and LTO/NCM type batteries as examples. Figure 3 shows the open circuit voltage (OCV) of battery C/LiFePO4 and LTO/NCM, as well as the corresponding SOC changes per mV voltage. From the graph, we can see that the slope of the OCV curve of LTO/NCM is relatively steep, and in most SOC ranges, the maximum SOC rate range corresponding to voltage changes per millivolt is less than 0.4% (except for SOC60-70%). Therefore, if the measurement accuracy of the battery voltage is 10mV, the SOC error obtained by the OCV estimation method is less than 4%. Therefore, regarding LTO/NCM batteries, the measurement accuracy of battery voltage should be less than 10mV. However, the slope of the C/LiFePO4OCV curve is relatively flat, and in most ranges (except for SOC<40% and 65-80%), the maximum corresponding SOC change rate per millivolt voltage reaches 4%. Therefore, the collection accuracy of battery voltage is required to be high, reaching around 1mV. At present, most of the collection accuracy of battery voltage is only 5mV. In references [47] and [48], voltage measurement methods for lithium-ion battery packs and fuel power battery packs were summarized, respectively. These methods include resistance voltage divider method, optocoupler isolation amplifier method, discrete transistor method [49], distributed measurement method [50], optocoupler relay method [51], and so on. At present, the voltage and temperature sampling of batteries has formed chip industrialization, and Table 1 compares the performance of most chips used in BMS.

3.2 Data sampling frequency synchronization

The sampling frequency and synchronization of signals have an impact on real-time data analysis and processing. When designing BMS, requirements should be put forward for the sampling frequency and synchronization accuracy of the signal. However, there are currently no clear requirements for signal sampling frequency and synchronization in some BMS design processes. There are various signals in the battery system, and the battery management system is generally distributed. If the current sampling and single chip voltage sampling are on different circuit boards; During the signal acquisition process, there may be synchronization issues with signals from different control sub boards, which can affect the real-time monitoring algorithm for internal resistance. The same single chip voltage collection sub board usually adopts a patrol method, and there may be synchronization issues between individual voltages, which affects inconsistency analysis. The system has different data sampling frequencies and synchronization requirements for different signals, and has lower requirements for parameters with high inertia. For example, the temperature rise order of 1 ℃/10min for normal discharge of pure electric vehicle batteries is considered. Considering temperature safety monitoring and the accuracy of BMS temperature (about 1 ℃), the temperature sampling interval can be set at 30 seconds (for hybrid lithium batteries, the temperature sampling rate is higher).

The voltage and current signals change rapidly, and the sampling frequency and synchronization requirements are very high. According to the analysis of AC impedance, the Ohmic internal resistance response of the power lithium battery is at the ms level, the SEI membrane ion transfer resistance voltage response is at the 10ms level, the charge transfer (double capacitance effect) response is at the 1-10s level, and the diffusion process response is at the min level. At present, when electric vehicles accelerate, the response time of the driving motor's current from the minimum to the maximum is about 0.5 seconds, and the current accuracy requirement is about 1%. Taking into account the variable load condition, the current sampling frequency should be 10-200Hz. The number of voltage channels on a single information collection sub board is generally a multiple of 6, with a maximum of 24 currently available. Generally, pure electric passenger car batteries consist of about 100 batteries connected in series, and single battery signal acquisition requires multiple acquisition sub boards. In order to ensure voltage synchronization, the smaller the voltage sampling time difference between individual units in each collection sub board, the better. It is best to have one inspection cycle within 25ms. The time synchronization between sub boards can be achieved by sending a CAN reference frame. The data update frequency should be above 10Hz.

The key functions of BMS that will be covered in the next two days' articles include: battery state estimation, including an overview of SOC estimation methods, SOH estimation methods, SOF estimation methods, battery consistency and equilibrium methods, and fault diagnosis overview.

3.3 Battery state estimation

The battery status includes battery temperature, SOC (state of charge estimation), SOH (health state estimation), SOS (safety state estimation), SOF (functional state estimation), and SOE (available energy state estimation). The relationship between various state estimations is shown in Figure 4. Battery temperature estimation is the foundation of other state estimation, and SOC estimation is influenced by SOH. SOF is determined by SOC, SOH, SOS, and battery temperature together, while SOE is related to SOC, SOH, battery temperature, and future operating conditions.

3.3.1 Battery temperature estimation

Temperature has a significant impact on battery performance, and currently only the surface temperature of the battery can be measured, while the internal temperature of the battery needs to be estimated using a thermal model. Common battery thermal models include zero dimensional models (lumped parameter models), one-dimensional and even three-dimensional models. The zero dimensional model can roughly calculate the temperature changes during the battery charging and discharging process, with limited estimation accuracy. However, the model has a small computational complexity, so it can be used for real-time temperature estimation. The one-dimensional, two-dimensional, and three-dimensional models need to use numerical methods to solve the heat transfer differential equations, grid the battery, calculate the temperature field distribution of the battery, and also consider the impact of the battery structure on heat transfer (including the core, shell, electrolyte layer, etc.). In the one-dimensional model, only the temperature distribution of the battery in one direction is considered to be uniform in other directions. The two-dimensional model considers the battery in two directions

For cylindrical battery, the axial and radial temperature distribution can reflect the temperature field inside the battery. A two-dimensional model is generally used for temperature analysis of thin film batteries. The three-dimensional model can fully reflect the temperature field inside the square battery, and the simulation accuracy is high, so there is more research. However, the computational complexity of 3D models is large and cannot be applied to real-time temperature estimation. They can only be used for temperature field simulation in the laboratory. In order to enable the real-time application of the calculation results of the 3D model, researchers used the temperature field calculation results of the 3D model to express the relationship between the battery heat generation power and the internal and external temperature difference using a transfer function. By estimating the internal temperature of the battery through the heat generation power and the battery surface temperature, there is potential for application in BMS. Figure 5 shows the estimation process of the internal temperature of the battery.

Generally, the suitable operating temperature for lithium-ion batteries is 15-35 ℃, while the actual operating temperature for electric vehicles is -30-50 ℃. Therefore, thermal management must be carried out on the battery, heating at low temperatures and cooling at high temperatures. Thermal management includes two aspects: design and control, among which thermal management design does not belong to the content of this article. The temperature control is to measure the temperature of different positions of the battery pack through the temperature measuring element, and integrate the temperature distribution. The control circuit of the thermal management system is used for heat dissipation. The executive components of the thermal management generally include fans, water/oil pumps, refrigerators, etc. For example, the temperature range can be divided into different levels for control. The thermal management of the Volt plug-in hybrid lithium battery is divided into three modes: active (cooling and heat dissipation), passive (fan heat dissipation), and non cooling mode. When the temperature of the power lithium battery exceeds a predetermined passive cooling target temperature, the passive heat dissipation mode is activated; When the temperature continues to rise above the target temperature for active cooling, the active cooling mode is activated.

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