CN109932663A - Battery state of health assessment method, device, storage medium and electronic device - Google Patents
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Abstract
本发明提供了一种电池健康状态评估方法、装置、存储介质及电子装置，其中，该方法包括：确定目标电池的电池参数，其中，所述电池参数包括所述目标电池的容量增量，所述目标电池的放电容量以及所述目标电池的电池内阻；使用第一模型对所述电池参数进行分析，确定所述目标电池的健康状态，其中，所述第一模型为使用多组数据通过机器学习训练出的，所述多组数据中的每组数据均包括：电池参数和电池的健康状态；输出用于标识所述目标电池的健康状态的标识信息。通过本发明，解决了相关技术中存在的无法实时且全面地评价电池的健康状态的问题。
The present invention provides a battery state of health assessment method, device, storage medium and electronic device, wherein the method includes: determining a battery parameter of a target battery, wherein the battery parameter includes a capacity increment of the target battery, and the the discharge capacity of the target battery and the battery internal resistance of the target battery; use the first model to analyze the battery parameters to determine the state of health of the target battery, wherein the first model uses multiple sets of data to pass Based on machine learning training, each of the multiple sets of data includes: battery parameters and battery health status; and output identification information for identifying the target battery health status. The present invention solves the problem in the related art that the state of health of the battery cannot be evaluated in real time and comprehensively.
Description
技术领域technical field
本发明涉及通信领域，具体而言，涉及一种电池健康状态评估方法、装置、存储介质及电子装置。The present invention relates to the field of communications, and in particular, to a method, a device, a storage medium and an electronic device for evaluating the state of health of a battery.
背景技术Background technique
随着电动汽车的不断推广，锂电池由于其绿色环保的性能，在电动汽车领域也得到了广泛的使用。动力电池是电动汽车的关键部件之一，动力电池技术极大影响这电动汽车的性能和成本。但是车载动力电池性能随着充放电循环而逐渐退化，一般认为当电池容量不足80％的时候，需要对电池进行更换或者维修保养，避免影响汽车行驶性能，杜绝安全隐患。因此需要对电动汽车用动力电池的健康状态(State of Health，将成为SOH)进行评估，及时让用户了解电池的健康状况，以便及时更换老化电池。With the continuous promotion of electric vehicles, lithium batteries have also been widely used in the field of electric vehicles due to their green performance. Power battery is one of the key components of electric vehicles, and power battery technology greatly affects the performance and cost of electric vehicles. However, the performance of the vehicle power battery gradually degrades with the charging and discharging cycle. It is generally believed that when the battery capacity is less than 80%, the battery needs to be replaced or repaired to avoid affecting the driving performance of the vehicle and prevent potential safety hazards. Therefore, it is necessary to evaluate the state of health (which will become SOH) of the power battery for electric vehicles, so as to let users know the health status of the battery in time, so as to replace the aging battery in time.
当前研究过程中，动力电池的健康状态评估方法一般分为两种，其一是采用基于容量的SOH定义，即用“当前放电容量”Ci与“初始放电容量”C0的比值表征电池的健康状态。另外一种方法是采用基于内阻的SOH定义(混合动力电动车)，基于电池模型，使用当前、寿命结束和全新时的电池内阻来表征电池健康度。In the current research process, the state of health assessment methods of power batteries are generally divided into two types. One is to use the capacity-based SOH definition, that is, the ratio of the "current discharge capacity" C i to the "initial discharge capacity" C 0 is used to characterize the battery's performance. health status. Another approach is to use the internal resistance-based SOH definition (hybrid electric vehicle), based on a battery model, using the current, end-of-life, and new battery internal resistance to characterize battery health.
需要说明的是，当前电池健康度的主要两个检测方法(即，基于容量SOH、基于内阻SOH)，通常用于实验室环境测试电池健康状态，需要专业人员、专业设备进行测试实验，较难实现在线实时监测。同时，动力电池的退化还受到环境、负载、振动、腐蚀等多种不确定因素的影响，单一使用上述的两个方法不能全面评价电池的健康状态。It should be noted that the current two main detection methods of battery health (namely, capacity-based SOH and internal resistance-based SOH) are usually used to test battery health status in laboratory environments, requiring professionals and professional equipment to conduct test experiments. It is difficult to realize online real-time monitoring. At the same time, the degradation of the power battery is also affected by various uncertain factors such as environment, load, vibration, corrosion, etc. The above two methods alone cannot fully evaluate the health status of the battery.
针对相关技术中存在的无法实时且全面地评价电池的健康状态的问题，目前尚未提出有效的解决方案。For the problem in the related art that the state of health of the battery cannot be evaluated in real time and comprehensively, no effective solution has been proposed yet.
发明内容SUMMARY OF THE INVENTION
本发明实施例提供了一种电池健康状态评估方法、装置、存储介质及电子装置，以至少解决相关技术中存在的无法实时且全面地评价电池的健康状态的问题。Embodiments of the present invention provide a method, device, storage medium and electronic device for evaluating the state of health of a battery, so as to at least solve the problem in the related art that the state of health of a battery cannot be evaluated in real time and comprehensively.
根据本发明的一个实施例，提供了一种电池健康状态评估方法，包括：确定目标电池的电池参数，其中，所述电池参数包括所述目标电池的容量增量，所述目标电池的放电容量以及所述目标电池的电池内阻；使用第一模型对所述电池参数进行分析，确定所述目标电池的健康状态，其中，所述第一模型为使用多组数据通过机器学习训练出的，所述多组数据中的每组数据均包括：电池参数和电池的健康状态；输出用于标识所述目标电池的健康状态的标识信息。According to an embodiment of the present invention, there is provided a battery state of health assessment method, comprising: determining a battery parameter of a target battery, wherein the battery parameter includes a capacity increment of the target battery, a discharge capacity of the target battery and the battery internal resistance of the target battery; use the first model to analyze the battery parameters to determine the health state of the target battery, wherein the first model is trained by using multiple sets of data through machine learning, Each of the multiple sets of data includes: battery parameters and the state of health of the battery; and output identification information for identifying the state of health of the target battery.
可选地，使用第一模型对所述电池参数进行分析，确定所述目标电池的健康状态包括：基于所述第一模型确定所述目标电池的电池参数中所包括的各参数对所述目标电池的健康状态的影响占比；基于各参数对应的影响占比确定所述目标电池的所述健康状态。Optionally, using the first model to analyze the battery parameters, and determining the state of health of the target battery includes: determining, based on the first model, that each parameter included in the battery parameters of the target battery affects the target battery. Influence ratio of the health state of the battery; the health state of the target battery is determined based on the influence ratio corresponding to each parameter.
可选地，所述第一模型是通过如下方式得到的：基于每组数据中包括的电池参数中的容量增量的曲线中的预定值与对应的电池的健康状态的关系得到容量增量指标，其中，所述曲线的预定值包括曲线峰高度，峰面积，峰左侧斜率以及峰右侧斜率；确定每组数据中包括的电池参数中的当前放电容量，将所述当前放电容量与所述多组数据中包括的电池参数中的初始放电容量的比值作为放电容量指标；确定每组数据中包括的电池参数中的当前电池的第一电阻，电池寿命用尽时的第二电阻以及电池的初始电阻，将所述第二电阻和所述第一电阻的差，与所述第二电阻和所述初始电阻的差的比值作为电池内阻指标；利用预定相关性分析方法对多组所述容量增量指标、所述放电容量指标以及所述电池内阻指标对电池的健康状态的影响占比进行分析，以得到最终的各电池参数对应的影响占比；将最终的各电池参数与各电池参数对应的影响占比的乘积之和作为所述第一模型。Optionally, the first model is obtained by: obtaining the capacity increment index based on the relationship between the predetermined value in the curve of the capacity increment in the battery parameters included in each set of data and the state of health of the corresponding battery. , wherein the predetermined values of the curve include the peak height, peak area, slope on the left side of the peak, and slope on the right side of the peak; determine the current discharge capacity in the battery parameters included in each set of data, and compare the current discharge capacity with all The ratio of the initial discharge capacity in the battery parameters included in the multiple sets of data is used as the discharge capacity index; the first resistance of the current battery in the battery parameters included in each set of data, the second resistance when the battery life is exhausted, and the battery are determined. The initial resistance of the battery, the ratio of the difference between the second resistance and the first resistance and the difference between the second resistance and the initial resistance is used as the battery internal resistance index; Analyze the influence ratio of the capacity increment index, the discharge capacity index and the battery internal resistance index on the health state of the battery to obtain the final influence ratio of each battery parameter; compare the final battery parameters with The sum of the products of the influence ratios corresponding to each battery parameter is used as the first model.
可选地，输出用于标识所述目标电池的健康状态的标识信息包括：将用于标识所述目标电池的健康状态的标识信息显示在预定终端的显示屏上。Optionally, outputting identification information for identifying the health state of the target battery includes: displaying the identification information for identifying the health state of the target battery on a display screen of a predetermined terminal.
可选地，在确定目标电池的电池参数之前，所述方法还包括：接收输入的用于查看所述目标电池的电池健康状态的查询请求，其中，所述查询请求用于触发执行确定所述目标电池的电池参数的确定操作。Optionally, before determining the battery parameters of the target battery, the method further includes: receiving an input query request for checking the battery state of health of the target battery, wherein the query request is used to trigger the execution of determining the Determination of battery parameters of the target battery.
根据本发明的另一个实施例，还提供了一种电池健康状态评估装置，包括：确定模块，用于确定目标电池的电池参数，其中，所述电池参数包括所述目标电池的容量增量，所述目标电池的放电容量以及所述目标电池的电池内阻；分析模块，用于使用第一模型对所述电池参数进行分析，确定所述目标电池的健康状态，其中，所述第一模型为使用多组数据通过机器学习训练出的，所述多组数据中的每组数据均包括：电池参数和电池的健康状态；输出模块，用于输出用于标识所述目标电池的健康状态的标识信息。According to another embodiment of the present invention, there is also provided a battery state of health assessment device, comprising: a determination module configured to determine a battery parameter of a target battery, wherein the battery parameter includes a capacity increment of the target battery, The discharge capacity of the target battery and the battery internal resistance of the target battery; an analysis module, configured to use a first model to analyze the battery parameters to determine the health state of the target battery, wherein the first model It is trained by using multiple sets of data through machine learning, and each set of data in the multiple sets of data includes: battery parameters and battery state of health; an output module for outputting a data used to identify the state of health of the target battery. identification information.
可选地，所述分析模块包括：第一确定单元，用于基于所述第一模型确定所述目标电池的电池参数中所包括的各参数对所述目标电池的健康状态的影响占比；第二确定单元，用于基于各参数对应的影响占比确定所述目标电池的所述健康状态。Optionally, the analysis module includes: a first determination unit, configured to determine, based on the first model, the proportion of the influence of each parameter included in the battery parameters of the target battery on the state of health of the target battery; The second determining unit is configured to determine the state of health of the target battery based on the influence ratio corresponding to each parameter.
可选地，所述输出模块包括：显示单元，用于将用于标识所述目标电池的健康状态的标识信息显示在预定终端的显示屏上。Optionally, the output module includes: a display unit configured to display identification information for identifying the health state of the target battery on a display screen of a predetermined terminal.
根据本发明的又一个实施例，还提供了一种存储介质，所述存储介质中存储有计算机程序，其中，所述计算机程序被设置为运行时执行上述任一项方法实施例中的步骤。According to yet another embodiment of the present invention, a storage medium is also provided, wherein a computer program is stored in the storage medium, wherein the computer program is configured to execute the steps in any one of the above method embodiments when running.
根据本发明的又一个实施例，还提供了一种电子装置，包括存储器和处理器，所述存储器中存储有计算机程序，所述处理器被设置为运行所述计算机程序以执行上述任一项方法实施例中的步骤。According to yet another embodiment of the present invention, there is also provided an electronic device comprising a memory and a processor, wherein the memory stores a computer program, the processor is configured to run the computer program to execute any of the above Steps in Method Examples.
通过本发明，基于大量的训练数据(例如，车联网数据)建立了用于评估电池的健康状态的评估模型，进而可以通过该模型来实时获取电池的健康状态，并且，在对电池的健康状态进行评估时，是基于多方面参数来综合评估的，因此，有效解决了相关技术中存在的无法实时且全面地评价电池的健康状态的问题，进而达到了可以实时且全面地评价电池的健康状态，从而使使用者能够全面了解电池的健康状态，并基于电池的健康状态来确定是否需要更换电池，保证了车辆的安全使用。Through the present invention, an evaluation model for evaluating the state of health of the battery is established based on a large amount of training data (for example, data of the Internet of Vehicles), and then the state of health of the battery can be obtained in real time through the model, and the state of health of the battery can be obtained in real time through the model. When evaluating, it is based on a comprehensive evaluation of various parameters. Therefore, it effectively solves the problem in the related art that the health state of the battery cannot be evaluated in real time and comprehensively, and thus achieves a real-time and comprehensive evaluation of the health state of the battery. , so that the user can fully understand the health state of the battery, and determine whether the battery needs to be replaced based on the health state of the battery, thereby ensuring the safe use of the vehicle.
附图说明Description of drawings
此处所说明的附图用来提供对本发明的进一步理解，构成本申请的一部分，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。在附图中：The accompanying drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the attached image:
图1是根据本发明实施例的电池健康状态评估方法的流程图；1 is a flowchart of a battery state of health assessment method according to an embodiment of the present invention;
图2是根据本发明实施例的系统图；2 is a system diagram according to an embodiment of the present invention;
图3是根据本发明实施例的电池健康状态综合评估模型图；FIG. 3 is a diagram of a comprehensive evaluation model of a battery state of health according to an embodiment of the present invention;
图4是根据本发明实施例查看当前车辆的电池健康信息的示意图；4 is a schematic diagram of viewing battery health information of a current vehicle according to an embodiment of the present invention;
图5是根据本发明实施例的电池健康状态评估装置的结构框图。FIG. 5 is a structural block diagram of a battery state of health assessment device according to an embodiment of the present invention.
具体实施方式Detailed ways
下文中将参考附图并结合实施例来详细说明本发明。需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。Hereinafter, the present invention will be described in detail with reference to the accompanying drawings and in conjunction with embodiments. It should be noted that the embodiments in the present application and the features of the embodiments may be combined with each other in the case of no conflict.
需要说明的是，本发明的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。It should be noted that the terms "first", "second" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence.
目前，国家电网初步建成了国际领先、功能强大、统一开放的车联网云平台，并以该平台为基础，构建了充电、出行和能源三大业务体系。车联网云平台累计接入充电桩总数已达几十万个。At present, State Grid has initially built an internationally leading, powerful, unified and open Internet of Vehicles cloud platform, and based on this platform, it has built three major business systems: charging, travel and energy. The total number of charging piles connected to the Internet of Vehicles cloud platform has reached hundreds of thousands.
在本发明实施例中，构建了基于车联网平台的动力电池健康状态评估系统，利用车联网平台的数据采集、存储及分析优势，以及车联网高性能云平台的计算效率，通过对动力电池大数据进行分析，训练动力电池健康度评估模型。通过车联网云平台接口，可以实时为普通车主用户提供详细的电池管理信息。此外，该系统还可以为汽车厂商提供电池老化数据，作为其研发改进的重要依据。In the embodiment of the present invention, a power battery health status assessment system based on the Internet of Vehicles platform is constructed, using the advantages of data collection, storage and analysis of the Internet of Vehicles platform, and the computing efficiency of the high-performance cloud platform of the Internet of Vehicles The data is analyzed, and the power battery health evaluation model is trained. Through the Internet of Vehicles cloud platform interface, detailed battery management information can be provided to ordinary car owners and users in real time. In addition, the system can also provide battery aging data for automakers as an important basis for their R&D improvements.
下面对本发明进行说明：The present invention is described below:
在本发明实施例中提出了一种电池健康度评估方法，该方法在前述两个现有的健康状态评估方法的基础上，加入了容量增量分析，并通过电池健康度影响因素相关性分析，计算各影响因素的权重因子，综合计算动力电池的健康度得分。In the embodiment of the present invention, a battery health evaluation method is proposed. The method adds capacity increment analysis on the basis of the aforementioned two existing health state evaluation methods, and analyzes the correlation of factors affecting the battery health degree. , calculate the weight factor of each influencing factor, and comprehensively calculate the health score of the power battery.
此外，训练动力电池健康度评估模型需要大量的电池数据，并需要高性能的计算平台，国网车联网平台同时满足这两个要求。目前，车联网平台主要用于智慧交通和绿色出行等方面。在本发明实施例中充分利用了该平台所采集的海量汽车数据，利用其高效的计算性能，评估电池健康度。充分挖掘车联网平台价值，为用户提供全方位的优质服务。In addition, training a power battery health assessment model requires a large amount of battery data and a high-performance computing platform. The State Grid Internet of Vehicles platform meets both requirements. At present, the Internet of Vehicles platform is mainly used for smart transportation and green travel. In the embodiment of the present invention, the massive vehicle data collected by the platform is fully utilized, and its efficient computing performance is utilized to evaluate the battery health. Fully tap the value of the Internet of Vehicles platform and provide users with a full range of high-quality services.
图1是根据本发明实施例的电池健康状态评估方法的流程图，如图1所示，该流程包括如下步骤：FIG. 1 is a flowchart of a battery state of health assessment method according to an embodiment of the present invention. As shown in FIG. 1 , the flowchart includes the following steps:
步骤S102，确定目标电池的电池参数，其中，所述电池参数包括所述目标电池的容量增量，所述目标电池的放电容量以及所述目标电池的电池内阻；Step S102, determining battery parameters of the target battery, wherein the battery parameters include the capacity increment of the target battery, the discharge capacity of the target battery, and the battery internal resistance of the target battery;
步骤S104，使用第一模型对所述电池参数进行分析，确定所述目标电池的健康状态，其中，所述第一模型为使用多组数据通过机器学习训练出的，所述多组数据中的每组数据均包括：电池参数和电池的健康状态；Step S104, using a first model to analyze the battery parameters to determine the health state of the target battery, wherein the first model is trained by using multiple sets of data through machine learning, and the Each set of data includes: battery parameters and battery health;
步骤S106，输出用于标识所述目标电池的健康状态的标识信息。Step S106, outputting identification information for identifying the state of health of the target battery.
其中，上述的多组数据可以通过前述的车联网平台获取，即，可以通过对利用了该平台所采集的海量汽车数据进行训练来得到上述第一模型。Wherein, the above-mentioned multiple sets of data can be obtained through the above-mentioned car networking platform, that is, the above-mentioned first model can be obtained by training the massive car data collected by using the platform.
此外，上述多组数据可以是根据车联网平台某车型(即，上述的目标电池所在的汽车的车型)的全体历史数据，利用相关性分析方法，分析各种影响因素对电池健康状态的影响占比，确定各评价指标的权重，训练电池健康度评估模型；在实际使用过程中，该评估模型根据单辆汽车的实测数据，评估汽车当前的健康状态(或者说评价电池当前的健康状态)。具体的系统图可以参见图2。In addition, the above-mentioned multiple sets of data may be based on the overall historical data of a certain vehicle model (that is, the vehicle type of the vehicle in which the target battery is located) on the Internet of Vehicles platform, using a correlation analysis method to analyze the impact of various influencing factors on the battery health status. The weight of each evaluation index is determined, and the battery health evaluation model is trained; in the actual use process, the evaluation model evaluates the current health state of the car (or evaluates the current state of health of the battery) based on the measured data of a single car. The specific system diagram can be seen in Figure 2.
通过本发明，基于大量的训练数据(例如，车联网数据)建立了用于评估电池的健康状态的评估模型，进而可以通过该模型来实时获取电池的健康状态，并且，在对电池的健康状态进行评估时，是基于多方面参数来综合评估的，因此，有效解决了相关技术中存在的无法实时且全面地评价电池的健康状态的问题，进而达到了可以实时且全面地评价电池的健康状态，从而使使用者能够全面了解电池的健康状态，并基于电池的健康状态来确定是否需要更换电池，保证了车辆的安全使用。Through the present invention, an evaluation model for evaluating the state of health of the battery is established based on a large amount of training data (for example, data of the Internet of Vehicles), and then the state of health of the battery can be obtained in real time through the model, and the state of health of the battery can be obtained in real time through the model. When evaluating, it is based on a comprehensive evaluation of various parameters. Therefore, it effectively solves the problem in the related art that the health state of the battery cannot be evaluated in real time and comprehensively, and thus achieves a real-time and comprehensive evaluation of the health state of the battery. , so that the user can fully understand the health state of the battery, and determine whether the battery needs to be replaced based on the health state of the battery, thereby ensuring the safe use of the vehicle.
在一个可选的实施例中，使用第一模型对所述电池参数进行分析，确定所述目标电池的健康状态包括：基于所述第一模型确定所述目标电池的电池参数中所包括的各参数对所述目标电池的健康状态的影响占比；基于各参数对应的影响占比确定所述目标电池的所述健康状态。In an optional embodiment, using a first model to analyze the battery parameters, and determining the state of health of the target battery includes: determining, based on the first model, each of the battery parameters included in the target battery The influence ratio of the parameter to the health state of the target battery; the health state of the target battery is determined based on the influence ratio corresponding to each parameter.
在一个可选的实施例中，所述第一模型是通过如下方式得到的：基于每组数据中包括的电池参数中的容量增量的曲线中的预定值与对应的电池的健康状态的关系得到容量增量指标，其中，所述曲线的预定值包括曲线峰高度，峰面积，峰左侧斜率以及峰右侧斜率；确定每组数据中包括的电池参数中的当前放电容量，将所述当前放电容量与所述多组数据中包括的电池参数中的初始放电容量的比值作为放电容量指标；确定每组数据中包括的电池参数中的当前电池的第一电阻，电池寿命用尽时的第二电阻以及电池的初始电阻，将所述第二电阻和所述第一电阻的差，与所述第二电阻和所述初始电阻的差的比值作为电池内阻指标；利用预定相关性分析方法对多组所述容量增量指标、所述放电容量指标以及所述电池内阻指标对电池的健康状态的影响占比进行分析，以得到最终的各电池参数对应的影响占比；将最终的各电池参数与各电池参数对应的影响占比的乘积之和作为所述第一模型。下面对各参数的具体计算方式进行举例说明：In an optional embodiment, the first model is obtained by the following manner: a relationship between a predetermined value in a curve of a capacity increment in a battery parameter included in each set of data and a corresponding state of health of the battery Obtain the capacity increment index, wherein the predetermined value of the curve includes the peak height of the curve, the peak area, the slope on the left side of the peak and the slope on the right side of the peak; determine the current discharge capacity in the battery parameters included in each set of data, and use the The ratio of the current discharge capacity to the initial discharge capacity in the battery parameters included in the multiple sets of data is used as a discharge capacity indicator; the first resistance of the current battery in the battery parameters included in each set of data is determined, and when the battery life is exhausted, the first resistance of the current battery is determined. For the second resistance and the initial resistance of the battery, the ratio of the difference between the second resistance and the first resistance and the difference between the second resistance and the initial resistance is used as the battery internal resistance index; the predetermined correlation is used to analyze The method analyzes the influence ratio of multiple groups of the capacity increment index, the discharge capacity index and the battery internal resistance index on the health state of the battery, so as to obtain the final influence proportion corresponding to each battery parameter; The sum of the products of each battery parameter of and the influence ratio corresponding to each battery parameter is used as the first model. The following is an example of the specific calculation method of each parameter:
图3是电池健康状态综合评估模型，在该模型中涉及到了模型训练阶段的多种电池参数的计算，包括：Figure 3 is a comprehensive evaluation model of battery state of health, which involves the calculation of various battery parameters in the model training phase, including:
①容量增量分析： ①Capacity increment analysis:
其中，Q为容量，V为电压，I为电流，t为时间。k为容量增量统计的开始时间，n为容量增量统计的截止时间，Δt为时间增量，ΔV为电压增量。容量增量曲线(IC曲线)可以体现三元锂离子电池的不同老化衰退模式，通过车联网平台的海量电池数据分析(主成分回归)IC曲线的几个典型特征(曲线峰高度Z1、峰面积Z2、峰左、右侧斜率Z3、Z4等)与动力电池健康度的关系，得到健康度综合评价模型的容量增量指标A(其中，a1-a4代表的是各个特征的权重)：Among them, Q is the capacity, V is the voltage, I is the current, and t is the time. k is the start time of the capacity increment statistics, n is the end time of the capacity increment statistics, Δt is the time increment, and ΔV is the voltage increment. The capacity increment curve (IC curve) can reflect the different aging and decay modes of the ternary lithium-ion battery. Through the massive battery data analysis (principal component regression) of the Internet of Vehicles platform, several typical characteristics of the IC curve (curve peak height Z 1 , peak The relationship between the area Z 2 , the left and right slopes of the peak Z 3 , Z 4 , etc.) and the health degree of the power battery, the capacity increment index A of the comprehensive evaluation model of the health degree is obtained (where a 1 -a 4 represent each feature the weight of):
A＝a1*Z1+a2*Z2+a3*Z3+a4*Z4 A=a 1 *Z 1 +a 2 *Z 2 +a 3 *Z 3 +a 4 *Z 4
②放电容量计算公式： ②Calculation formula of discharge capacity:
离散化计算公式： The discretization calculation formula:
其中，t0为放电初始时间，t1为放电截止时间，n为不同时间增量下的电流。使用放电容量离散化公式分析计算动力电池当前的放电容量，用“当前放电容量”Ci与“初始放电容量”C0的比值表征电池健康度综合评价模型的放电容量指标B：Among them, t 0 is the initial discharge time, t 1 is the discharge end time, and n is the current at different time increments. The current discharge capacity of the power battery is analyzed and calculated using the discharge capacity discretization formula, and the ratio of the "current discharge capacity" C i to the "initial discharge capacity" C 0 is used to represent the discharge capacity index B of the comprehensive evaluation model of battery health:
③电池内阻计算(根据电压差与电流差计算动态电阻)： ③Calculation of battery internal resistance (calculate dynamic resistance according to voltage difference and current difference):
电池内阻根据实际测得的电压、电流数据，利用最小二乘法或者卡尔曼滤波等方法计算得到。基于内阻的SOH定义方式，计算得到电池健康度综合评价模型的电池内阻指标C：The internal resistance of the battery is calculated by the method of least squares or Kalman filter according to the actual measured voltage and current data. Based on the SOH definition method of internal resistance, the battery internal resistance index C of the comprehensive evaluation model of battery health is calculated:
式中，Ri、Rn、R0分别表示当前、寿命结束和全新时的电池内阻。In the formula, R i , R n , and R 0 represent the current, end-of-life and new battery internal resistances, respectively.
最后，车联网平台根据大量历史电池数据，使用皮尔逊相关系数等相关性分析方法，分析以上A、B、C三个评价指标对电池健康度的影响程度，得到一个综合动力电池健康度评价模型：Finally, based on a large amount of historical battery data, the Internet of Vehicles platform uses correlation analysis methods such as Pearson correlation coefficient to analyze the impact of the above three evaluation indicators A, B, and C on battery health, and obtains a comprehensive power battery health evaluation model :
SOH＝α*A+β*B+γ*CSOH=α*A+β*B+γ*C
在得到上述模型之后，可以进入健康度评估阶段，即，采集单辆汽车动力电池数据，通过训练好的评估模型，对单辆汽车的健康度进行评估。After the above model is obtained, the health degree evaluation stage can be entered, that is, the data of the power battery of a single vehicle is collected, and the health degree of a single vehicle is evaluated through the trained evaluation model.
在相关技术中，普通车主一般较难获取汽车的电池的健康状态，普通汽车用户与车联网的交互不足。本发明基于车联网云平台接口，设计电动汽车动力电池信息可视化管理系统，用户移动终端从车联网平台获取数据，通过图表等友好方式为用户提供电池信息。在一个可选的实施例中，输出用于标识所述目标电池的健康状态的标识信息包括：将用于标识所述目标电池的健康状态的标识信息显示在预定终端的显示屏上。从而可以使得用户通过该系统实时查看电池的健康状态。在本发明实施例中，用户可以通过移动终端向车联网发起数据查询请求，车联网平台服务器端返回移动终端车辆动力电池实时的健康状态评分，以及其他常规电池信息。在本实施例中，用户可以通过移动终端随时接入系统，查看当前车辆的电池健康信息，如图4所示。In the related art, it is generally difficult for ordinary car owners to obtain the health status of the car's battery, and the interaction between ordinary car users and the Internet of Vehicles is insufficient. The invention designs a visual management system for electric vehicle power battery information based on the Internet of Vehicles cloud platform interface. The user mobile terminal obtains data from the Internet of Vehicles platform, and provides battery information to users in friendly ways such as charts. In an optional embodiment, outputting the identification information for identifying the state of health of the target battery includes: displaying the identification information for identifying the state of health of the target battery on a display screen of a predetermined terminal. Therefore, the user can view the health status of the battery in real time through the system. In the embodiment of the present invention, the user can initiate a data query request to the Internet of Vehicles through the mobile terminal, and the server of the Internet of Vehicles platform returns the real-time health status score of the vehicle power battery of the mobile terminal and other conventional battery information. In this embodiment, the user can access the system at any time through a mobile terminal to view the current vehicle battery health information, as shown in FIG. 4 .
在一个可选的实施例中，在确定目标电池的电池参数之前，所述方法还包括：接收输入的用于查看所述目标电池的电池健康状态的查询请求，其中，所述查询请求用于触发执行确定所述目标电池的电池参数的确定操作。在本实施例中，可以根据输入的查询请求来执行当前的电池的健康状态评估操作。In an optional embodiment, before determining the battery parameters of the target battery, the method further includes: receiving an input query request for checking the battery health status of the target battery, wherein the query request is used for Trigger to perform a determination operation of determining the battery parameters of the target battery. In this embodiment, the current battery state of health assessment operation may be performed according to the input query request.
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到根据上述实施例的方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本发明各个实施例所述的方法。From the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is better implementation. Based on this understanding, the technical solutions of the present invention can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products are stored in a storage medium (such as ROM/RAM, magnetic disk, CD-ROM), including several instructions to make a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention.
在本实施例中还提供了一种电池健康状态评估装置，该装置用于实现上述实施例及优选实施方式，已经进行过说明的不再赘述。如以下所使用的，术语“模块”可以实现预定功能的软件和/或硬件的组合。尽管以下实施例所描述的装置较佳地以软件来实现，但是硬件，或者软件和硬件的组合的实现也是可能并被构想的。This embodiment also provides a battery state of health assessment device, which is used to implement the above embodiments and preferred implementations, and what has been described will not be repeated. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, implementations in hardware, or a combination of software and hardware, are also possible and contemplated.
图5是根据本发明实施例的电池健康状态评估装置的结构框图，如图5所示，该装置包括:5 is a structural block diagram of a battery state of health assessment device according to an embodiment of the present invention. As shown in FIG. 5 , the device includes:
确定模块52，用于确定目标电池的电池参数，其中，所述电池参数包括所述目标电池的容量增量，所述目标电池的放电容量以及所述目标电池的电池内阻；A determination module 52, configured to determine battery parameters of the target battery, wherein the battery parameters include the capacity increment of the target battery, the discharge capacity of the target battery, and the battery internal resistance of the target battery;
分析模块54，用于使用第一模型对所述电池参数进行分析，确定所述目标电池的健康状态，其中，所述第一模型为使用多组数据通过机器学习训练出的，所述多组数据中的每组数据均包括：电池参数和电池的健康状态；The analysis module 54 is configured to use a first model to analyze the battery parameters and determine the health state of the target battery, wherein the first model is trained by using multiple sets of data through machine learning, and the multiple sets of data are Each group of data in the data includes: battery parameters and battery health status;
输出模块56，用于输出用于标识所述目标电池的健康状态的标识信息。The output module 56 is configured to output identification information for identifying the health state of the target battery.
在一个可选的实施例中，所述分析模块54包括：第一确定单元，用于基于所述第一模型确定所述目标电池的电池参数中所包括的各参数对所述目标电池的健康状态的影响占比；第二确定单元，用于基于各参数对应的影响占比确定所述目标电池的所述健康状态。In an optional embodiment, the analysis module 54 includes: a first determination unit, configured to determine, based on the first model, the health of the target battery by each parameter included in the battery parameters of the target battery The influence ratio of the state; the second determination unit is configured to determine the health state of the target battery based on the influence ratio corresponding to each parameter.
在一个可选的实施例中，所述第一模型是通过如下方式得到的：基于每组数据中包括的电池参数中的容量增量的曲线中的预定值与对应的电池的健康状态的关系得到容量增量指标，其中，所述曲线的预定值包括曲线峰高度，峰面积，峰左侧斜率以及峰右侧斜率；确定每组数据中包括的电池参数中的当前放电容量，将所述当前放电容量与所述多组数据中包括的电池参数中的初始放电容量的比值作为放电容量指标；确定每组数据中包括的电池参数中的当前电池的第一电阻，电池寿命用尽时的第二电阻以及电池的初始电阻，将所述第二电阻和所述第一电阻的差，与所述第二电阻和所述初始电阻的差的比值作为电池内阻指标；利用预定相关性分析方法对多组所述容量增量指标、所述放电容量指标以及所述电池内阻指标对电池的健康状态的影响占比进行分析，以得到最终的各电池参数对应的影响占比；将最终的各电池参数与各电池参数对应的影响占比的乘积之和作为所述第一模型。In an optional embodiment, the first model is obtained by the following manner: a relationship between a predetermined value in a curve of a capacity increment in a battery parameter included in each set of data and a corresponding state of health of the battery Obtain the capacity increment index, wherein the predetermined value of the curve includes the peak height of the curve, the peak area, the slope on the left side of the peak and the slope on the right side of the peak; determine the current discharge capacity in the battery parameters included in each set of data, and use the The ratio of the current discharge capacity to the initial discharge capacity in the battery parameters included in the multiple sets of data is used as a discharge capacity indicator; the first resistance of the current battery in the battery parameters included in each set of data is determined, and when the battery life is exhausted, the first resistance of the current battery is determined. For the second resistance and the initial resistance of the battery, the ratio of the difference between the second resistance and the first resistance and the difference between the second resistance and the initial resistance is used as the battery internal resistance index; the predetermined correlation is used to analyze The method analyzes the influence ratio of multiple groups of the capacity increment index, the discharge capacity index and the battery internal resistance index on the health state of the battery, so as to obtain the final influence proportion corresponding to each battery parameter; The sum of the products of each battery parameter of and the influence ratio corresponding to each battery parameter is used as the first model.
在一个可选的实施例中，所述输出模块56包括：显示单元，用于将用于标识所述目标电池的健康状态的标识信息显示在预定终端的显示屏上。In an optional embodiment, the output module 56 includes: a display unit, configured to display the identification information for identifying the health state of the target battery on the display screen of the predetermined terminal.
在一个可选的实施例中，所述装置还用于在确定目标电池的电池参数之前，接收输入的用于查看所述目标电池的电池健康状态的查询请求，其中，所述查询请求用于触发执行确定所述目标电池的电池参数的确定操作。In an optional embodiment, the apparatus is further configured to, before determining the battery parameters of the target battery, receive an input query request for checking the battery health status of the target battery, wherein the query request is used for Trigger to perform a determination operation of determining the battery parameters of the target battery.
需要说明的是，上述各个模块是可以通过软件或硬件来实现的，对于后者，可以通过以下方式实现，但不限于此：上述模块均位于同一处理器中；或者，上述各个模块以任意组合的形式分别位于不同的处理器中。It should be noted that the above modules can be implemented by software or hardware, and the latter can be implemented in the following ways, but not limited to this: the above modules are all located in the same processor; or, the above modules can be combined in any combination The forms are located in different processors.
本发明的实施例还提供了一种存储介质，该存储介质中存储有计算机程序，其中，该计算机程序被设置为运行时执行上述任一项方法实施例中的步骤。An embodiment of the present invention further provides a storage medium, where a computer program is stored in the storage medium, wherein the computer program is configured to execute the steps in any one of the above method embodiments when running.
可选地，在本实施例中，上述存储介质可以包括但不限于：U盘、只读存储器(Read-Only Memory，简称为ROM)、随机存取存储器(Random Access Memory，简称为RAM)、移动硬盘、磁碟或者光盘等各种可以存储计算机程序的介质。Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (Read-Only Memory, referred to as ROM), a random access memory (Random Access Memory, referred to as RAM), Various media that can store computer programs, such as removable hard disks, magnetic disks, or optical disks.
本发明的实施例还提供了一种电子装置，包括存储器和处理器，该存储器中存储有计算机程序，该处理器被设置为运行计算机程序以执行上述任一项方法实施例中的步骤。An embodiment of the present invention also provides an electronic device, comprising a memory and a processor, where a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any of the above method embodiments.
可选地，上述电子装置还可以包括传输设备以及输入输出设备，其中，该传输设备和上述处理器连接，该输入输出设备和上述处理器连接。Optionally, the above-mentioned electronic device may further include a transmission device and an input-output device, wherein the transmission device is connected to the above-mentioned processor, and the input-output device is connected to the above-mentioned processor.
可选地，本实施例中的具体示例可以参考上述实施例及可选实施方式中所描述的示例，本实施例在此不再赘述。Optionally, for specific examples in this embodiment, reference may be made to the examples described in the foregoing embodiments and optional implementation manners, and details are not described herein again in this embodiment.
由上述实施例可知，本发明的目的在于通过车联网数据建立动力电池健康评估模型，用户可以通过移动终端随时接入系统，查看当前车辆的电池健康信息。可以实现如下有益效果：As can be seen from the above embodiments, the purpose of the present invention is to establish a power battery health assessment model through the data of the Internet of Vehicles, and the user can access the system at any time through a mobile terminal to view the current vehicle battery health information. The following beneficial effects can be achieved:
基于车联网平台，对动力电池的健康状态进行评估，及时提醒车主对电池进行保养，或者更换老化电池；Based on the Internet of Vehicles platform, the health status of the power battery is evaluated, and the owner is reminded to maintain the battery or replace the aging battery in time;
考虑多种电池健康度影响因素，分析各种影响因素对电池健康度的影响程度，综合计算影响度的权重，提出一种更加合理、准确的电池健康状态评价方法；Considering various influencing factors of battery health, analyze the influence degree of various influencing factors on battery health, comprehensively calculate the weight of influence, and propose a more reasonable and accurate battery health evaluation method;
系统的分析结果可以为车厂研发人员提供重要的实际电池数据支持，帮助进行产品优化改进；The analysis results of the system can provide important actual battery data support for the R&D personnel of the car factory, and help to optimize and improve the product;
移动端可视化系统方便普通车主及时从车联网平台获取车辆电池信息，具有良好的可扩展性，后期可根据需求添加更多功能。The mobile terminal visualization system is convenient for ordinary car owners to obtain vehicle battery information from the car networking platform in time. It has good scalability, and more functions can be added later as needed.
此外，还需要说明的是，本发明实施例中的方案可以是基于车联网平台对电动汽车数据进行存储以及分析，也可以是基于其他云计算平台实现该系统。In addition, it should also be noted that the solution in the embodiment of the present invention may be based on the Internet of Vehicles platform to store and analyze the electric vehicle data, and may also implement the system based on other cloud computing platforms.
显然，本领域的技术人员应该明白，上述的本发明的各模块或各步骤可以用通用的计算装置来实现，它们可以集中在单个的计算装置上，或者分布在多个计算装置所组成的网络上，可选地，它们可以用计算装置可执行的程序代码来实现，从而，可以将它们存储在存储装置中由计算装置来执行，并且在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤，或者将它们分别制作成各个集成电路模块，或者将它们中的多个模块或步骤制作成单个集成电路模块来实现。这样，本发明不限制于任何特定的硬件和软件结合。Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general-purpose computing device, which can be centralized on a single computing device, or distributed in a network composed of multiple computing devices Alternatively, they may be implemented in program code executable by a computing device, such that they may be stored in a storage device and executed by the computing device, and in some cases, in a different order than here The steps shown or described are performed either by fabricating them separately into individual integrated circuit modules, or by fabricating multiple modules or steps of them into a single integrated circuit module. As such, the present invention is not limited to any particular combination of hardware and software.
以上所述仅为本发明的优选实施例而已，并不用于限制本发明，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention shall be included within the protection scope of the present invention.
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Cited By (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110441706A (en) * | 2019-08-23 | 2019-11-12 | 优必爱信息技术（北京）有限公司 | A kind of battery SOH estimation method and equipment |
| CN110596594A (en) * | 2019-09-23 | 2019-12-20 | 广东毓秀科技有限公司 | A method of predicting the SOE of rail transit lithium battery through big data |
| CN110907844A (en) * | 2019-11-19 | 2020-03-24 | 北京汽车股份有限公司 | Vehicle-mounted storage battery state detection method and device, readable storage medium and vehicle |
| CN111006834A (en) * | 2019-12-24 | 2020-04-14 | 汕头大学 | Method for real-time monitoring and evaluation of battery collision damage based on sensor signals |
| CN111142038A (en) * | 2019-12-31 | 2020-05-12 | 浙江吉利新能源商用车集团有限公司 | Storage battery health state assessment method and device |
| CN111308354A (en) * | 2020-03-11 | 2020-06-19 | 深圳易马达科技有限公司 | Method and device for detecting state of health of battery, electronic equipment and storage medium |
| CN111398833A (en) * | 2020-03-13 | 2020-07-10 | 浙江大学 | Battery health state evaluation method and evaluation system |
| CN111458643A (en) * | 2020-05-22 | 2020-07-28 | 清华四川能源互联网研究院 | Abnormal battery screening method, device, electronic device and readable storage medium |
| CN112529464A (en) * | 2020-12-23 | 2021-03-19 | 东软睿驰汽车技术（沈阳）有限公司 | Health degree evaluation method and device of battery pack and related product |
| CN112666473A (en) * | 2020-11-04 | 2021-04-16 | 深圳市科陆电子科技股份有限公司 | Battery detection method and battery detection system |
| CN112946483A (en) * | 2021-02-05 | 2021-06-11 | 重庆长安新能源汽车科技有限公司 | Comprehensive evaluation method for battery health of electric vehicle and storage medium |
| FR3106415A1 (en) | 2020-01-21 | 2021-07-23 | IFP Energies Nouvelles | Rapid and offline diagnostic procedures for accumulators and associated devices |
| CN114358967A (en) * | 2020-09-27 | 2022-04-15 | 北京新能源汽车股份有限公司 | A battery safety assessment method, device, equipment and medium |
| WO2022143903A1 (en) * | 2020-12-31 | 2022-07-07 | 奥动新能源汽车科技有限公司 | Safety evaluation method and system for vehicle battery, and device and readable storage medium |
| CN115219936A (en) * | 2022-07-18 | 2022-10-21 | 东软睿驰汽车技术（沈阳）有限公司 | A method and apparatus for quantifying the influence of different factors on battery health |
| CN115236540A (en) * | 2021-04-22 | 2022-10-25 | 北京骑胜科技有限公司 | Health status quantification method, health status quantification device, health status storage medium and computer program product |
| WO2022242058A1 (en) * | 2021-05-21 | 2022-11-24 | 北京理工大学 | Battery state of health estimation method for real new energy vehicle |
| CN115622203A (en) * | 2022-12-15 | 2023-01-17 | 深圳市百度电子有限公司 | Analysis reminding method and system based on charging data of vehicle-mounted wireless charger |
| CN116599191A (en) * | 2023-07-17 | 2023-08-15 | 深圳市菲尼基科技有限公司 | Energy management method, device, equipment and storage medium based on energy storage inverter |
| WO2023207403A1 (en) * | 2022-04-24 | 2023-11-02 | 深圳市道通科技股份有限公司 | Traction battery data stream diagnosis visualization method and diagnosis device |
| CN117851179A (en) * | 2024-01-15 | 2024-04-09 | 上海异工同智信息科技有限公司 | Portable equipment system health state detection and evaluation method and system |
| CN118033461A (en) * | 2024-02-29 | 2024-05-14 | 广东电网有限责任公司 | A battery health status assessment method, device and electronic equipment |
| WO2024140475A1 (en) * | 2022-12-28 | 2024-07-04 | 华为技术有限公司 | Battery evaluation method and related apparatus |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103558556A (en) * | 2013-10-31 | 2014-02-05 | 重庆长安汽车股份有限公司 | Power battery SOH estimation method |
| CN106896273A (en) * | 2015-12-18 | 2017-06-27 | 北汽福田汽车股份有限公司 | The internal resistance detection method of battery cell, detection means and the vehicle with it |
| CN108680869A (en) * | 2018-06-29 | 2018-10-19 | 上海科列新能源技术有限公司 | A kind of appraisal procedure and device of power battery health status |
| CN108872861A (en) * | 2018-04-27 | 2018-11-23 | 温州大学 | A kind of method of online evaluation cell health state |
| CN108896926A (en) * | 2018-07-18 | 2018-11-27 | 湖南宏迅亿安新能源科技有限公司 | A kind of appraisal procedure, assessment system and the associated component of lithium battery health status |
| CN109031153A (en) * | 2018-10-16 | 2018-12-18 | 北京交通大学 | A kind of health status On-line Estimation method of lithium ion battery |
-
2019
- 2019-03-07 CN CN201910171177.0A patent/CN109932663A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103558556A (en) * | 2013-10-31 | 2014-02-05 | 重庆长安汽车股份有限公司 | Power battery SOH estimation method |
| CN106896273A (en) * | 2015-12-18 | 2017-06-27 | 北汽福田汽车股份有限公司 | The internal resistance detection method of battery cell, detection means and the vehicle with it |
| CN108872861A (en) * | 2018-04-27 | 2018-11-23 | 温州大学 | A kind of method of online evaluation cell health state |
| CN108680869A (en) * | 2018-06-29 | 2018-10-19 | 上海科列新能源技术有限公司 | A kind of appraisal procedure and device of power battery health status |
| CN108896926A (en) * | 2018-07-18 | 2018-11-27 | 湖南宏迅亿安新能源科技有限公司 | A kind of appraisal procedure, assessment system and the associated component of lithium battery health status |
| CN109031153A (en) * | 2018-10-16 | 2018-12-18 | 北京交通大学 | A kind of health status On-line Estimation method of lithium ion battery |
Non-Patent Citations (1)
| Title |
|---|
| 郭琦沛 等: ""基于容量增量曲线的三元锂离子电池健康状态估计方法"", 《全球能源互联网》 * |
Cited By (29)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN111398833A (en) * | 2020-03-13 | 2020-07-10 | 浙江大学 | Battery health state evaluation method and evaluation system |
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