WO2020186550A1 - 一种基于气液动力学模型的电池开路电压估算方法及装置 - Google Patents

一种基于气液动力学模型的电池开路电压估算方法及装置 Download PDF

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WO2020186550A1
WO2020186550A1 PCT/CN2019/080284 CN2019080284W WO2020186550A1 WO 2020186550 A1 WO2020186550 A1 WO 2020186550A1 CN 2019080284 W CN2019080284 W CN 2019080284W WO 2020186550 A1 WO2020186550 A1 WO 2020186550A1
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circuit voltage
open circuit
open
battery
estimation
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陈彪
江浩斌
孙化阳
栗欢欢
华蕾
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Jiangsu University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/374—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] with means for correcting the measurement for temperature or ageing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/3644—Constructional arrangements
    • G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm

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  • the invention belongs to the field of battery management systems, and in particular relates to a method and device for estimating open circuit voltage of a battery based on a gas-liquid dynamic model.
  • Oil is called black gold and the blood of industry, but oil resources will gradually be exhausted as humans continue to exploit them.
  • Transportation accounts for nearly half of the total oil consumption.
  • countries all over the world are striving to find alternative oil energy sources.
  • vigorously developing electric vehicle technology is one of the important choices.
  • the current battery model generally has problems such as complex models and unstable parameter changes, which lead to inaccurate estimates of the open circuit voltage (OCV) of the battery and difficult to determine the remaining cruising range. Therefore, it is of great significance to establish an accurate battery model.
  • the electrochemical model studies the charging and discharging process from the essence of the battery, and describes the macroscopic (such as voltage, current, resistance, etc.) and microscopic (ion concentration distribution, transmission, etc.) related to battery design parameters through equations of state, differential equations and partial differential equations.
  • the equivalent circuit model studies the charging and discharging process from the perspective of the external characteristics of the battery. Electronic components can intuitively describe the charging and discharging process, such as capacitance, resistance and ideal power supply, and its state equation is simpler than the electrochemical model.
  • Equivalent circuit models have many forms and structures, such as Rint model, Thevenin model, PNGV, n-RC model and so on.
  • the Rint model is very simple, but the SOC estimation accuracy is unsatisfactory. On the contrary, blindly pursuing accuracy will produce more uncertain parameters that need to be identified, such as the third-order RC equivalent circuit model.
  • the equivalent circuit model is often combined with intelligent algorithms, such as sliding film algorithm, fuzzy logic algorithm, simulated annealing algorithm, particle swarm algorithm, Kalman filter or its variant algorithm. The intelligent algorithm needs to do a lot of calculations, which also makes it difficult for the model to realize real-time estimation on the on-board MCU.
  • the present invention provides a method and device for estimating the open circuit voltage of a battery based on a gas-liquid dynamics model.
  • the open circuit voltage estimation equation in the present invention includes the battery temperature and does not need to be coupled with the battery temperature to simplify the estimation process of the open circuit voltage;
  • the gas dissolution/precipitation principle in the equation is equivalent to the battery polarization effect, which better fits the phenomenon that the open circuit voltage lags behind the battery terminal voltage;
  • the estimation result of the estimation equation does not depend on the accuracy of the input initial value, and has excellent estimation robustness It can more accurately describe the non-linear process of battery charging and discharging, the analytical formula is simple, the parameter identification is easy, the amount of calculation is small, and it reflects the influence of battery temperature characteristics on the open circuit voltage, which is convenient for implementation in engineering.
  • a method for estimating the open circuit voltage of a battery based on a gas-liquid dynamics model includes the following steps:
  • Step 1 derive the open circuit voltage estimation equation to be determined according to the aero-hydraulic dynamic model
  • Step 2 Identify and estimate equation parameters based on experimental data: Obtain the corresponding open circuit voltages at different currents, terminal voltages, and temperatures through experimental tests, and identify the optimal values of the parameters to be determined in the open circuit voltage estimation equation through the identification method. The optimal value is substituted into the open-circuit voltage estimation equation to be determined in step 1 to obtain a complete open-circuit voltage estimation equation;
  • Step 3 Design an open-circuit voltage estimation method based on the complete open-circuit voltage estimation equation, and calculate the estimated value of the open-circuit voltage.
  • the open circuit voltage estimation equation in the first step is:
  • P 0 , I and P 1 represent terminal voltage, current and open circuit voltage respectively
  • P 3 represents the open circuit voltage to be estimated
  • T represents the battery temperature
  • ⁇ airflow density
  • ⁇ airflow resistance coefficient
  • k the first equivalent parameter
  • L the second equivalent parameter
  • P 0 the pressure of the nozzle
  • P 2 the pressure of the gas in the container during the filling/deflation of the gas-liquid dynamics model.
  • step three the specific process of step three is:
  • the identification method is genetic algorithm, particle swarm algorithm, simulated annealing algorithm, ant colony algorithm, support vector machine method, neural network algorithm or least square method.
  • a device for implementing the method for estimating the open circuit voltage of a battery based on a gas-liquid dynamics model comprising a signal acquisition component, an open circuit voltage estimation component and a display component;
  • the signal collection component is used to collect the current, temperature and voltage of the battery
  • the signal acquisition component is connected to the open circuit voltage estimation component and transmits the collected current, temperature and voltage signals to the open circuit voltage estimation component, and the open circuit voltage estimation component calculates the open circuit voltage value according to the open circuit voltage estimation equation;
  • the open circuit voltage estimation component is connected to the display component, and sends the battery current, temperature, voltage and open circuit voltage values to the display component for display.
  • the signal acquisition component includes a current sensor, a temperature sensor, and a voltage sensor;
  • the current sensor is used to detect the current of the battery
  • the temperature sensor is used to detect the temperature of the battery
  • the voltage sensor is used to detect the voltage of the battery.
  • the open circuit voltage estimation component includes a single-chip microcomputer.
  • the OCV estimation equation of the present invention is simple, decoupled from time, has a small amount of calculation, can eliminate errors through iteration, has high estimation accuracy, and can realize real-time estimation of open circuit voltage on a single-chip microcomputer.
  • the temperature of the present invention is the same as the terminal voltage and current as the input of the OCV estimation equation, without introducing temperature compensation coefficients or empirical formulas, reducing the difficulty of parameter identification and improving the robustness of OCV estimation.
  • the aero-hydraulic dynamics model of the present invention is simple, intuitive and easy to understand, and reflects the characteristic that the battery terminal voltage lags behind the open circuit voltage.
  • Figure 1 is a flow chart of the inventive method.
  • Figure 2 shows the physical quantity diagram of the gas-liquid dynamics model.
  • Figure 3 shows the charge and discharge cut-off voltage of a common secondary battery.
  • Figure 4 is a flowchart of parameter identification.
  • Figure 5 shows the values of the parameters to be identified in the open circuit voltage estimation equation.
  • Figure 6 is a flow chart for estimating OCV.
  • Figure 7 is a block diagram of the OCV estimation device.
  • Figure 8 shows the estimated results at 15°C.
  • Figure 9 shows the estimated error at 15°C.
  • Figure 10 shows the estimated results at 25°C.
  • Figure 11 shows the estimated error at 25°C.
  • Figure 12 shows the estimated results at 35°C.
  • Figure 13 shows the estimated error at 35°C.
  • Figure 14 shows the estimated result at 45°C.
  • Figure 15 shows the estimated error at 45°C.
  • first and second are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined with “first” and “second” may explicitly or implicitly include one or more of these features. In the description of the present invention, “plurality” means two or more than two, unless specifically defined otherwise.
  • the terms “installed”, “connected”, “connected”, “fixed” and other terms should be understood in a broad sense, for example, it can be a fixed connection or a detachable connection. , Or integrally connected; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and it can be the internal communication between two components.
  • installed can be a fixed connection or a detachable connection.
  • it can be a mechanical connection or an electrical connection
  • it can be directly connected, or indirectly connected through an intermediate medium, and it can be the internal communication between two components.
  • the specific meaning of the above-mentioned terms in the present invention can be understood according to specific circumstances.
  • Fig. 1 shows an embodiment of the method for estimating open circuit voltage of a battery based on a gas-liquid dynamics model according to the present invention.
  • the method for estimating open circuit voltage of a battery based on the aerodynamic model includes the following steps:
  • Step 1 derive the open circuit voltage estimation equation to be determined according to the aero-hydraulic dynamic model
  • the physical prototype of the gas-liquid dynamics model is a closed container equipped with a gas-liquid coexistence system.
  • the container contains a volume V, a pressure P, a substance quantity n, and an average temperature T.
  • Compressed gas and liquid with a volume of V w , n j represents the amount of substance dissolved in the gas in the liquid;
  • the top of the container is equipped with an elbow and a valve that can be opened and closed. If the valve is opened, the gas in the container can be released or outside
  • the gas is pumped into the container;
  • the letters ⁇ and ⁇ are respectively the comprehensive resistance coefficient and density of the pipeline during the gas flow process, and the letters I and P 0 represent the gas flow rate and the pressure of the nozzle respectively.
  • the charging current is positive and the discharging current is negative;
  • the state equations of the gas-liquid dynamics model include: ideal gas state equation, gas dissolution equilibrium equation and Bernoulli equation;
  • P 0 , I and P 1 respectively represent the nozzle pressure, gas flow rate and gas pressure in the container in the steady state in the gas-liquid dynamics model.
  • they correspond to the terminal voltage, current and open circuit voltage.
  • P 3 is in the gas
  • the hydrodynamic model represents the steady-state pressure in the container to be estimated.
  • it represents the open circuit voltage to be estimated.
  • T In the hydrodynamic model, it represents the gas temperature in the container. In the battery, it represents the battery temperature, ⁇ : Airflow density, ⁇ : airflow resistance coefficient, k: the first equivalent parameter, l: the second equivalent parameter, P 0 : nozzle pressure, P 2 : gas pressure in the container during filling/deflation of the gas-liquid dynamics model ;
  • step one The specific process of step one is:
  • P 1 gas pressure in the container under steady state
  • P 2 gas pressure in the container during filling/deflation
  • P 3 pressure in the container under steady state to be estimated
  • n 2 container during filling/deflation
  • T the temperature of the gas in the container
  • V the volume of gas
  • R the thermodynamic constant
  • V W the volume of liquid
  • b m the gas molecule
  • n j1 the amount of substances dissolved in the gas in the liquid in the steady state
  • n j3 the amount of substances dissolved in the gas in the liquid in the steady state to be estimated
  • the amount of material n 2 , n 3 , n j1 and n j3 satisfy the control relationship:
  • n 3 n 2 +n j1 -n j3 formula seven
  • any two voltage values can be selected in the common secondary battery charging and discharging window, and the double voltage value must be greater than the double voltage value, as shown in Figure 3, then 2P 1 -P 2 > 0, And because all physical quantities are greater than zero, then ⁇ >0, ac ⁇ 0 is always established.
  • the quadratic equation is obtained, that is, formula eleven must have a single positive real root, so:
  • Formula 1 and Formula 2 are open-circuit voltage estimation equations, where the charging current is positive and the discharging current is negative;
  • Step 2 Identify the parameters of the estimated equation based on the experimental data: There are four undetermined parameters in the open-circuit voltage estimation equation of Step 1, namely k, l, ⁇ and ⁇ . Different currents and terminals are obtained through experimental tests through variable magnification and variable temperature HPPC. The corresponding open circuit voltage at voltage and temperature, and the optimal identification method is solved by genetic algorithm to identify the optimal values of the k, l, ⁇ and ⁇ parameters in the open circuit voltage estimation equation, and the values of the k, l, ⁇ and ⁇ parameters are substituted in The open-circuit voltage estimation equation to be determined in step one obtains a complete open-circuit voltage estimation equation; the identification process is shown in Figure 4, and the identification result is shown in Figure 5;
  • the identification method is genetic algorithm, particle swarm algorithm, simulated annealing algorithm, ant colony algorithm, support vector machine method, neural network algorithm or least square method.
  • genetic algorithm is preferred.
  • Step 3 Design the open-circuit voltage estimation method according to the complete open-circuit voltage estimation equation, and calculate the estimated value of the open-circuit voltage, as shown in Figure 6, the specific process is:
  • a device for implementing the method for estimating the open circuit voltage of a battery based on the gas-liquid dynamics model includes a signal acquisition component, an open circuit voltage estimation component, and a display component; the signal acquisition component is used to collect battery current , Temperature and voltage; the signal acquisition component is connected to the open circuit voltage estimation component and transmits the collected current, temperature and voltage signals to the open circuit voltage estimation component, and the open circuit voltage estimation component calculates the open circuit voltage value according to the open circuit voltage estimation equation; The open circuit voltage estimation component is connected to the display component, and sends the battery current, temperature, voltage and open circuit voltage values to the display component for display.
  • the signal acquisition component includes a current sensor, a temperature sensor and a voltage sensor.
  • the open circuit voltage estimation component includes a single-chip microcomputer, and the single-chip microcomputer is preferably an STM32.
  • the battery OCV estimation method based on the gas-liquid dynamics model is implemented on hardware, which can be implemented on the STM32 single-chip microcomputer using the code written in C language on the Keil uVision5 development platform.
  • the open circuit voltage estimation component is specifically:
  • the acquisition card can directly collect the voltage of the single battery.
  • the voltage range of the single battery is within 0-5V;
  • the acquisition card is connected to the serial port of the STM single-chip microcomputer, and the communication method is RS-232, which transmits the current, voltage and temperature signals of the battery to the single-chip microcomputer;
  • STM32 microcontroller reads the battery's current, voltage, and temperature signals, and calls the OCV estimation function to calculate the open circuit voltage value under the current input; writes the battery current, voltage, temperature and the calculated open circuit voltage value into the memory card, and writes the battery The current, voltage, temperature and the calculated open circuit voltage value are sent to the display part of the host computer for display;
  • the host computer is developed based on the Microsoft Visual Studio platform, and is used to display the terminal voltage of the battery pack, the open circuit voltage, the open circuit voltage of all series-connected single cells, and the minimum open circuit voltage of the fitted battery;
  • the signal communication protocols used include: RS-485, CAN, TCP, modbus, MPI, serial communication, etc.
  • the normal operating temperature of electric vehicle batteries is 15°C to 45°C.
  • the present invention chooses 15°C as the starting temperature, and the estimated results are verified at 0.1C, 0.3C, 0.5C, 1C and 2C magnifications at intervals of 10°C, as shown in the figure Shown in 8-15.
  • the normal operating temperature of electric vehicle batteries is 15°C to 45°C.
  • the present invention chooses 15°C as the starting temperature, and the estimated results are verified at 0.1C, 0.3C, 0.5C, 1C and 2C magnifications at intervals of 10°C, as shown in the figure Shown in 8-15.
  • Fig. 8 shows the model estimation effect under 15°C environment
  • Fig. 8 shows the model estimation effect under 15°C environment
  • FIG. 8 shows that the estimation curve basically coincides with the experimental curve
  • Fig. 9 is the estimation error corresponding to Fig. 8
  • Fig. 9 shows the estimation results at each magnification after the estimation is stable except for the final moment.
  • the estimation errors are all within ⁇ 20mV, which can meet the needs of real vehicles
  • Figure 10 shows the model estimation effect under 25°C environment
  • Figure 10 shows that the estimation curve basically coincides with the experimental curve
  • Figure 11 is the estimation error corresponding to Figure 10.
  • 11 shows that the estimation error at each magnification is within ⁇ 20mV after the estimation is stabilized at the end time, which can meet the needs of actual vehicle use
  • Figure 12 shows the model estimation effect under a 35°C environment
  • Figure 12 shows that the estimated curve and the experimental curve basically coincide.
  • Figure 13 is the estimation error corresponding to Figure 12.
  • Figure 13 shows that the estimation error at each magnification is within ⁇ 20mV after the estimation is stabilized at the end time, which can meet the actual vehicle usage requirements;
  • Figure 14 is the model estimation under 45°C environment Fig. 14 shows that the estimated curve basically coincides with the experimental curve.
  • Fig. 15 is the estimation error corresponding to Fig. 14.
  • Fig. 15 shows that the estimation error at each magnification is within ⁇ 20mV except at the end time after the estimation is stable. Demand for car use.

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Abstract

一种基于气液动力学模型的电池开路电压估算方法及装置，该方法包括：依据气液动力学模型推导出待定的开路电压估算方程；依据实验数据辨识估算方程参数；依据完备的开路电压估算方程设计开路电压估算方法，并计算得到开路电压估算值。其中的开路电压估算方程包含电池温度，无需再与电池温度耦合，简化开路电压估算过程；估算方程中气体溶解/析出原理等效于电池极化效应，更好地拟合开路电压滞后电池端电压现象；估算方程的估算结果不依赖于输入初值的精度，具有极好的估算鲁棒性；能够更准确地刻画电池充放电非线性过程、解析式简单、参数辨识容易、运算量小，且反映电池温度特性对开路电压的影响，便于在工程中实现。

Description

一种基于气液动力学模型的电池开路电压估算方法及装置 技术领域
本发明属于电池管理系统领域，具体涉及一种基于气液动力学模型的电池开路电压估算方法及装置。
背景技术
石油被称为黑色的黄金、工业的血液，但石油资源随着人类不断地开采将逐渐走向枯竭。交通占石油总消费比重接近一半，世界各国都在努力寻找可替代石油的能源，其中，大力发展电动汽车技术是重要选择之一。但是车载锂电池在使用过程中，由于放电深度的增加、内部活性物质的减少、EIS膜变厚内阻增大、可逆容量衰减和环境温度的变化等原因导致电池内部一些重要性能参数发生较大变化，而现阶段电池模型普遍存在模型复杂，参数变化不稳定等问题，导致电池开路电压OCV(Open Circuit Voltage)估算不准确，剩余续航里程难以确定。因此，建立准确的电池模型有着重要的意义。
目前，研究最多的电池解析模型为等效电路模型和电化学模型两种。电化学模型从电池的本质研究充放电过程，通过状态方程、微分方程和偏微分方程等描述与电池设计参数有关的宏观(如电压、电流、电阻等)及微观(离子浓度分布、传输等)信息，尽管刻画准确，但是巨大的复杂度和计算耗时等缺点，很难用于车载MCU实时估计。等效电路模型从电池外特性角度研究充放电过程，电子元件能够直观地描述充放电过程，如电容、电阻和理想电源，并且其状态方程比电化学模型简单。等效电路模型有很多形式和结构，如Rint model,Thevenin model,PNGV,n-RC model and so on。其中，Rint模型非常简单，但是SOC估算精度令人不满意。相反，盲目地追求精度将产生更多不确定的参数需要去辨识，如三阶RC等效电路模型。另外，为了在整个SOC过程中保证估算的精度，等效电路模型经常和智能算法结合，如滑膜算法、模糊逻辑算法、模拟退火算法、粒子群算法、卡尔曼滤波或其变体算法。而智能算法需要做大量的运算，同样使得该模型难以在车载MCU上实现实时估计。
综上所述，仅依赖现有的电池模型远不能达到实际应用的要求，急需一种能够更准确地刻画电池充放电非线性过程、反映电池温度特性、解析式简单、运算量小的模型和开路电压估算方法及装置。
发明内容
针对上述问题，本发明提供一种基于气液动力学模型的电池开路电压估算方法及装置，本发明中的开路电压估算方程包含电池温度，无需再与电池温度耦合，简化开路电压估算过 程；估算方程中气体溶解/析出原理等效于电池极化效应，更好地拟合开路电压滞后电池端电压现象；估算方程的估算结果不依赖于输入初值的精度，具有极好的估算鲁棒性；能够更准确地刻画电池充放电非线性过程、解析式简单、参数辨识容易、运算量小，且反映电池温度特性对开路电压的影响，便于在工程中实现。
本发明解决其技术问题所采用的技术方案是：
一种基于气液动力学模型的电池开路电压估算方法，具体包括如下步骤：
步骤一，依据气液动力学模型推导出待定的开路电压估算方程；
步骤二，依据实验数据辨识估算方程参数：通过实验测试获得不同电流、端电压、温度下对应的开路电压，并通过辨识方法辨识出开路电压估算方程中待定参数的最优值，将待定参数的最优值代入步骤一的待定开路电压估算方程得到完备的开路电压估算方程；
步骤三，依据完备的开路电压估算方程设计开路电压估算方法，并计算得到开路电压估算值。
上述方案中，
所述步骤一中的开路电压估算方程为：
Figure PCTCN2019080284-appb-000001
其中，
Figure PCTCN2019080284-appb-000002
P 0、I和P 1分别表示端电压、电流和开路电压，P 3表示要估算的开路电压，T：表示电池温度，ρ：气流密度，μ：气流阻力系数，k：第一等效参数，l：第二等效参数，P 0：管口压强；P 2：气液动力学模型充/放气过程中容器内气体压强。
上述方案中，所述步骤二中辨识估算方程参数具体过程为：
①读取开路电压OCV、端电压U、电流I、温度T数据；
②向OCV估算方程中P 1赋初值，即P 1＝OCV(1)，设置N＝1；
③赋值，P 0＝U(N),I＝I(N),T＝T(N)；
④设置待辨识参数k、l、ρ和μ条件大于或等于0；
⑤带入待定开路电压估算方程；
⑥更新初值P 1与N，P 1＝P 3，N＝N+1；
⑦将估算总误差S＝S+│P 3-OCV(N)│作为目标函数；
⑧直到S不再变小为判断终止条件；
⑨循环上述③至⑧步直至参数辨识结束，输出最优参数的值k、l、ρ和μ。
上述方案中，所述步骤三具体过程为：
①读取端电压U、电流I、温度T数据；
②向完备的开路电压估算方程中P 1赋初值，即P 1＝OCV(1)，设置N＝1；
③赋值，P 0＝U(N),I＝I(N),T＝T(N)；
④带入完备的开路电压估算方程中；
⑤更新初值P 1与N并输出估算出的开路电压值；
⑥循环③至⑤步直至开路电压估算结束。
上述方案中，所述辨识方法为遗传算法、粒子群算法、模拟退火算法、蚁群算法、支持向量机法、神经网络算法或最小二乘法。
一种实现所述基于气液动力学模型的电池开路电压估算方法的装置，包括信号采集部件、开路电压估算部件和显示部件；
所述信号采集部件用于采集电池的电流、温度和电压；
所述信号采集部件与开路电压估算部件连接并将采集的电流、温度和电压信号传送到开路电压估算部件，所述开路电压估算部件根据开路电压估算方程计算出开路电压值；
所述开路电压估算部件与显示部件连接，将电池电流、温度、电压和开路电压值发送给显示部件显示。
上述方案中，所述信号采集部件包括电流传感器、温度传感器和电压传感器；
所述电流传感器用于检测电池的电流；
所述温度传感器用于检测电池的温度；
所述电压传感器用于检测电池的电压。
上述方案中，所述开路电压估算部件包括单片机。
有技术相比，本发明的有益效果是：
1.本发明OCV估算方程简单、与时间解耦、计算量小，能够通过迭代消除误差，估算精度高，能在单片机上实现开路电压实时估算。
2.本发明温度与端电压、电流一样作为OCV估算方程输入量，无需引入温度补偿系数或经验公式，降低参数识别难度，提高OCV估算鲁棒性。
3.本发明所述气液动力学模型简单直观、易于理解，反映了电池端电压滞后开路电压的特性。
附图说明
本发明的上述和/或附加的方面和优点从结合下面附图对实施例的描述中将变得明显和容易理解，其中：
图1为发明方法流程图。
图2为气液动力学模型物理量图。
图3为常见二次电池充电与放电截止电压。
图4为参数辨识流程图。
图5为开路电压估算方程中待辨识参数的值。
图6为估算OCV流程图。
图7为OCV估算装置框图。
图8为在15℃下估算结果。
图9为在15℃下估算误差。
图10为在25℃下估算结果。
图11为在25℃下估算误差。
图12为在35℃下估算结果。
图13为在35℃下估算误差。
图14为在45℃下估算结果。
图15为在45℃下估算误差。
具体实施方式
下面详细描述本发明的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本发明，而不能理解为对本发明的限制。
在本发明的描述中，需要理解的是，术语“中心”、“纵向”、“横向”、“长度”、“宽度”、“厚度”、“上”、“下”、“轴向”、“径向”、“竖直”、“水平”、“内”、“外”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本发明和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本发明的限制。此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。在本发明的描述中，“多个”的含义是两个或两个以上，除非另有明确具体的限定。
在本发明中，除非另有明确的规定和限定，术语“安装”、“相连”、“连接”、“固 定”等术语应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是机械连接，也可以是电连接；可以是直接相连，也可以通过中间媒介间接相连，可以是两个元件内部的连通。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本发明中的具体含义。
图1所示为本发明所述基于气液动力学模型的电池开路电压估算方法的一种实施方式，所述基于气液动力学模型的电池开路电压估算方法包括以下步骤：
步骤一，依据气液动力学模型推导出待定的开路电压估算方程；
如图2所示，所述气液动力学模型的物理原型为设有气液共存系统的一个密闭容器，容器内装有体积为V、压强为P、物质的量为n、平均温度为T的压缩气体和体积为V w的液体，n j表示溶解于液体中气体的物质的量；容器顶部设有弯管和可开闭的阀门，如果打开阀门，容器内的气体能够放出来或是外界气体被泵入容器内；字母μ和ρ分别为气体流动过程中管道的综合阻力系数和密度，字母I和P 0分别表示气体的流速和管口的压强。
Figure PCTCN2019080284-appb-000003
其中，
Figure PCTCN2019080284-appb-000004
充电电流为正，放电电流为负；
所述气液动力学模型的状态方程包括：理想气体状态方程、气体溶解平衡方程和伯努利方程；
其中，P 0、I和P 1在气液动力学模型中分别表示管口压强、气体流速和稳态下容器内气体压强，在电池中分别对应端电压、电流和开路电压，P 3在气液动力学模型中表示要估算的稳态下容器内压强，在电池中表示要估算的开路电压，T：在气液动力学模型中表示容器内气体温度，在电池中表示电池温度，ρ：气流密度，μ：气流阻力系数，k：第一等效参数，l：第二等效参数，P 0：管口压强，P 2：气液动力学模型充/放气过程中容器内气体压强；
所述步骤一具体过程为：
理想气体状态方程：
P 2V＝n 2RT   公式三
P 3V＝n 3RT   公式四
气体溶解平衡方程：
Figure PCTCN2019080284-appb-000005
Figure PCTCN2019080284-appb-000006
其中，P 1：稳态下容器内气体压强，P 2：充/放气过程中容器内气体压强，P 3：要估算的稳态下容器内压强，n 2：充/放气过程中容器内气体物质的量，n 3：要估算的稳态下容器内气体物质的量，T：容器内气体温度，V：气体体积，R：热力学常数，V W：液体体积，b m:气体分子的范德华体积，
Figure PCTCN2019080284-appb-000007
有效间隙度，n j1：稳态下溶解于液体中气体的物质的量，n j3：要估算的稳态下溶解于液体中气体的物质的量；
其中，物质的量n 2、n 3、n j1和n j3满足控制关系为：
n 3＝n 2+n j1-n j3   公式七
其中，由公式三至公式七推导得出：
Figure PCTCN2019080284-appb-000008
将公式八化简得：
Figure PCTCN2019080284-appb-000009
设：
Figure PCTCN2019080284-appb-000010
整理得公式十一是关于P 3的二次方程：
Figure PCTCN2019080284-appb-000011
设：
Figure PCTCN2019080284-appb-000012
Figure PCTCN2019080284-appb-000013
Figure PCTCN2019080284-appb-000014
考虑电池实际物理意义，在常见二次电池充放电窗口内任取两个电压值，其中两倍电压值一定大于一倍的电压值，如图3所示，则2P 1-P 2＞0，又因为所有物理量均大于零，那么Δ＞0,ac＜0恒成立，依据韦达定理得到二次方程式即公式十一必存在唯一正实根，得：
Figure PCTCN2019080284-appb-000015
气体在流动过程中可以写出伯努利方程：
Figure PCTCN2019080284-appb-000016
公式一和公式二为开路电压估算方程，其中充电电流为正，放电电流为负；
步骤二，依据实验数据辨识估算方程参数：在步骤一的开路电压估算方程中有四个待定参数，分别为k、l、ρ和μ，通过变倍率变温度HPPC通过实验测试获得不同电流、端电压、温度下对应的开路电压，并通过遗传算法求解最优的辨识方法辨识出开路电压估算方程中k、l、ρ和μ参数的最优值，k、l、ρ和μ参数的值代入步骤一的待定开路电压估算方程得到完备的开路电压估算方程；辨识过程如图4所示，辨识结果如图5所示；
所述步骤二中辨识估算方程参数具体过程为：
①读取开路电压OCV、端电压U、电流I、温度T数据；
②向OCV估算方程中P 1赋初值，即P 1＝OCV(1)，设置N＝1；
③赋值，P 0＝U(N),I＝I(N),T＝T(N)；
④设置待辨识参数k、l、ρ和μ条件大于或等于0；
⑤带入待定开路电压估算方程；
⑥更新初值P 1与N，P 1＝P 3，N＝N+1；
⑦将估算总误差S＝S+│P 3-OCV(N)│作为目标函数；
⑧直到S不再变小为判断终止条件；
⑨循环上述③至⑧步直至参数辨识结束，输出最优参数的值k、l、ρ和μ；
所述辨识方法为遗传算法、粒子群算法、模拟退火算法、蚁群算法、支持向量机法、神经网络算法或最小二乘法。本实施例中优选为遗传算法。
步骤三，依据完备的开路电压估算方程设计开路电压估算方法，并计算得到开路电压估 算值，如图6所示，具体过程为：
①读取端电压U、电流I、温度T数据；
②向完备的开路电压估算方程中P 1赋初值，即P 1＝OCV(1)，设置N＝1；
③赋值，P 0＝U(N),I＝I(N),T＝T(N)；
④带入完备的开路电压估算方程中；
⑤更新初值P 1与N并输出估算出的开路电压值；
⑥循环③至⑤步直至开路电压估算结束。
如图7所示，一种实现所述基于气液动力学模型的电池开路电压估算方法的装置，包括信号采集部件、开路电压估算部件和显示部件；所述信号采集部件用于采集电池的电流、温度和电压；所述信号采集部件与开路电压估算部件连接并将采集的电流、温度和电压信号传送到开路电压估算部件，所述开路电压估算部件根据开路电压估算方程计算出开路电压值；所述开路电压估算部件与显示部件连接，将电池电流、温度、电压和开路电压值发送给显示部件显示。
所述信号采集部件包括电流传感器、温度传感器和电压传感器。
所述开路电压估算部件包括单片机，所述单片机优选为STM32。将基于气液动力学模型的电池OCV估算方法在硬件上实现，可以在Keil uVision5开发平台上运用C语言编写的代码在STM32单片机上实现的。
所述开路电压估算部件具体为：
首先加载STM32单片机库函数文件，运用库函数配置STM32单片机寄存器，编写时钟函数、定时器函数、延迟函数、存储函数、数据校验函数、OCV估算函数和主函数；
①将电流传感器、温度传感器连接到信号采集卡上，采集卡可以直接采集单体电池电压，优选的，单体电池电压范围在0—5V以内；
②采集卡与STM单片机串口相连，通讯方式选择RS-232，将电池的电流、电压、温度信号传给单片机；
③STM32单片机主函数读取电池的电流、电压、温度信号，调用OCV估算函数算出当前输入下的开路电压值；将电池电流、电压、温度和算出的开路电压值写入内存卡中，并把电池电流、电压、温度和算出的开路电压值发送给上位机的显示部件显示；
④如此循环第①—③步，完成电池组实时开路电压估算。
所述上位机是基于Microsoft Visual Studio平台开发的，用于显示电池组端电压、开路电压、所有串联单体电池的开路电压和拟合的电池最低开路电压；
所述单片机包括：2 n位单片机，n＝1,2,3...,以及各种ARM内核的运算单元；
运用的信号通讯协议包括：RS-485、CAN、TCP、modbus、MPI、串口通信等。
电动汽车电池正常工作温度为15℃至45℃，本发明选择以15℃为起始温度，每间隔10℃分别在0.1C、0.3C、0.5C、1C和2C倍率下验证估算结果，如图8-15所示。电动汽车电池正常工作温度为15℃至45℃，本发明选择以15℃为起始温度，每间隔10℃分别在0.1C、0.3C、0.5C、1C和2C倍率下验证估算结果，如图8-15所示。其中，图8为15℃环境下模型估算效果，图8显示估算曲线与实验曲线基本重合，图9是与图8相对应的估算误差，图9显示除了终了时刻在估算稳定之后各倍率下的估算误差均在±20mV以内，能够满足实车使用需求；图10为25℃环境下模型估算效果，图10显示估算曲线与实验曲线基本重合，图11是与图10相对应的估算误差，图11显示除了终了时刻在估算稳定之后各倍率下的估算误差均在±20mV以内，能够满足实车使用需求；图12为35℃环境下模型估算效果，图12显示估算曲线与实验曲线基本重合，图13是与图12相对应的估算误差，图13显示除了终了时刻在估算稳定之后各倍率下的估算误差均在±20mV以内，能够满足实车使用需求；图14为45℃环境下模型估算效果，图14显示估算曲线与实验曲线基本重合，图15是与图14相对应的估算误差，图15显示除了终了时刻在估算稳定之后各倍率下的估算误差均在±20mV以内，能够满足实车使用需求。
应当理解，虽然本说明书是按照各个实施例描述的，但并非每个实施例仅包含一个独立的技术方案，说明书的这种叙述方式仅仅是为清楚起见，本领域技术人员应当将说明书作为一个整体，各实施例中的技术方案也可以经适当组合，形成本领域技术人员可以理解的其他实施方式。
上文所列出的一系列的详细说明仅仅是针对本发明的可行性实施例的具体说明，它们并非用以限制本发明的保护范围，凡未脱离本发明技艺精神所作的等效实施例或变更均应包含在本发明的保护范围之内。

Claims (8)

  1. 一种基于气液动力学模型的电池开路电压估算方法，特征在于，具体包括如下步骤：
    步骤一，依据气液动力学模型推导出待定的开路电压估算方程；
    步骤二，依据实验数据辨识估算方程参数：通过实验测试获得不同电流、端电压、温度下对应的开路电压，并通过辨识方法辨识出开路电压估算方程中待定参数的最优值，将待定参数的最优值代入步骤一的待定开路电压估算方程得到完备的开路电压估算方程；
    步骤三，依据完备的开路电压估算方程设计开路电压估算方法，并计算得到开路电压估算值。
  2. 根据权利要求1所述的基于气液动力学模型的电池开路电压估算方法，其特征在于，所述步骤一中的开路电压估算方程为：
    Figure PCTCN2019080284-appb-100001
    其中，
    Figure PCTCN2019080284-appb-100002
    P 0、I和P 1分别表示端电压、电流和开路电压，P 3表示要估算的开路电压，T：表示电池温度，ρ：气流密度，μ：气流阻力系数，k：第一等效参数，l：第二等效参数，P 0：管口压强；P 2：气液动力学模型充/放气过程中容器内气体压强。
  3. 根据权利要求2所述的基于气液动力学模型的电池开路电压估算方法，其特征在于，所述步骤二中辨识估算方程参数具体过程为：
    ①读取开路电压OCV、端电压U、电流I、温度T数据；
    ②向OCV估算方程中P 1赋初值，即P 1＝OCV(1)，设置N＝1；
    ③赋值，P 0＝U(N),I＝I(N),T＝T(N)；
    ④设置待辨识参数k、l、ρ和μ条件大于或等于0；
    ⑤带入待定开路电压估算方程；
    ⑥更新初值P 1与N，P 1＝P 3，N＝N+1；
    ⑦将估算总误差S＝S+│P 3-OCV(N)│作为目标函数；
    ⑧直到S不再变小为判断终止条件；
    ⑨循环上述③至⑧步直至参数辨识结束，输出最优参数的值k、l、ρ和μ。
  4. 根据权利要求2所述的基于气液动力学模型的电池开路电压估算方法，其特征在于，所述步骤三具体过程为：
    ①读取端电压U、电流I、温度T数据；
    ②向完备的开路电压估算方程中P 1赋初值，即P 1＝OCV(1)，设置N＝1；
    ③赋值，P 0＝U(N),I＝I(N),T＝T(N)；
    ④带入完备的开路电压估算方程中；
    ⑤更新初值P 1与N并输出估算出的开路电压值；
    ⑥循环③至⑤步直至开路电压估算结束。
  5. 根据权利要求1所述的基于气液动力学模型的电池开路电压估算方法，其特征在于，所述辨识方法为遗传算法、粒子群算法、模拟退火算法、蚁群算法、支持向量机法、神经网络算法或最小二乘法。
  6. 一种实现权利要求1-5任意一项所述基于气液动力学模型的电池开路电压估算方法的装置，其特征在于，包括信号采集部件、开路电压估算部件和显示部件；
    所述信号采集部件用于采集电池的电流、温度和电压；
    所述信号采集部件与开路电压估算部件连接并将采集的电流、温度和电压信号传送到开路电压估算部件，所述开路电压估算部件根据开路电压估算方程计算出开路电压值；
    所述开路电压估算部件与显示部件连接，将电池电流、温度、电压和开路电压值发送给显示部件显示。
  7. 根据权利要求6所述基于气液动力学模型的电池开路电压估算方法的装置，其特征在于，所述信号采集部件包括电流传感器、温度传感器和电压传感器；
    所述电流传感器用于检测电池的电流；
    所述温度传感器用于检测电池的温度；
    所述电压传感器用于检测电池的电压。
  8. 根据权利要求6所述基于气液动力学模型的电池开路电压估算方法的装置，其特征在于，所述开路电压估算部件包括单片机。
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