Integrated new energy automobile battery detection system and device with equalization function

Abstract

The embodiment of the invention discloses an integrated new energy automobile battery detection system and device with an equalization function. The battery detection system comprises a battery data monitoring module, a battery state analysis module, an equalization charging planning module and a battery information feedback module. The battery data monitoring module performs charging and discharging data monitoring on a vehicle battery and performs cloud storage; the battery state analysis module constructs an analysis model based on operation data such as charging and discharging temperature, voltage and current and depends on existing detection data to analyze the comprehensive loss condition of the current vehicle battery; the equalization charging planning module comprehensively evaluates the health state of the vehicle battery and plans an equalization charging scheme according to an evaluation result; and the battery information feedback module is used for backing up and recording the comprehensive loss analysis data of the vehicle battery, feeding back the health state of the vehicle battery and outputting an equalizing charging scheme.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of new energy vehicles, and in particular to an integrated new energy vehicle battery detection system and device with a balancing function. Background Art

[0002] Battery testing for new energy vehicles refers to the use of a series of scientific methods and standards to evaluate and test the system performance and safety of the power batteries in pure electric vehicles, so as to ensure the reliability and safety of the power batteries in the process of storing and releasing electric energy, and to promptly discover and eliminate potential safety hazards;

[0003] At present, new energy vehicles are rapidly promoted in various regions, accounting for a large proportion of travel vehicles. As the power source of new energy vehicles, the safety testing of the power battery is particularly important. The power battery needs to be tested repeatedly not only during the production process, but also during the use process after leaving the factory;

[0004] However, in the current environment, new energy vehicle users lack effective means of observing the real-time status of the power battery. They can only make indirect inferences based on the battery life experience or vehicle driving experience, or understand the status through regular maintenance, and lack timely understanding of the power battery status. In addition, the current charging plan for the power battery is relatively simple, and it is impossible to plan charging for different battery states. Summary of the invention

[0005] The embodiment of the present invention provides an integrated new energy vehicle battery detection system and device with a balancing function, so as to obtain the battery status of the new energy vehicle in real time and accurately, and plan the charging of the vehicle battery according to the loss and health status of the battery.

[0006] In a first aspect, an embodiment of the present invention provides an integrated new energy vehicle battery detection system with a balancing function, including a battery data monitoring module, a battery status analysis module, a balancing charging planning module, and a battery information feedback module;

[0007] The battery data monitoring module is used to monitor the charge and discharge data of the vehicle battery corresponding to the operation cycle under the vehicle operation state, and construct a charge and discharge data set of the vehicle battery corresponding to the operation cycle for cloud storage;

[0008] Among them, battery data monitoring includes charge and discharge data monitoring and battery information collection; charge and discharge data monitoring includes collecting indicator data during the charge and discharge process of electric vehicle power batteries, including charge and discharge current, charge and discharge voltage, maximum single power battery voltage, rated capacity of the whole vehicle power battery system, rated total voltage of the whole vehicle power battery system, nominal total energy of the power battery, current state of charge SOC, terminated state of charge SOC, maximum power battery temperature, maximum allowable charging voltage of single battery, maximum allowable total charging voltage, cumulative charging time, output energy, etc.;

[0009] Battery information collection includes collecting the power battery data of the tested vehicle, including battery type, battery voltage, battery power, battery capacity, protocol version, manufacturer, production date, VIN, software version, charging status, report number, etc.

[0010] The battery status analysis module is electrically connected to the battery data monitoring module and the balanced charging planning module respectively, and is used to analyze the charging and discharging data set of the vehicle battery, and to construct a curve model to analyze the comprehensive loss of the vehicle battery in the corresponding operation cycle in combination with the battery discharge prediction loss of the vehicle battery;

[0011] The balanced charging planning module is used to evaluate the battery health status of the vehicle battery in the corresponding operation cycle based on the comprehensive loss of the vehicle battery in the corresponding operation cycle, and plan a corresponding balanced charging plan;

[0012] The battery information feedback module is electrically connected to the battery status analysis module and the balanced charging planning module respectively, and is used to feed back and output the comprehensive loss situation of the vehicle battery corresponding to the operation cycle, and the corresponding planned balanced charging plan.

[0013] Optionally, the battery data monitoring module includes a battery data acquisition unit and a data integration processing unit;

[0014] The battery data acquisition unit is used to monitor the charge and discharge data of the vehicle battery corresponding to the operation cycle under the vehicle operation state, and store the data in the cloud through cloud transmission;

[0015] The data integration processing unit is electrically connected to the battery data acquisition unit and the battery status analysis module respectively. The data integration processing unit is used to integrate the charging and discharging data of the vehicle battery corresponding to the operating cycle based on the operating cycle label, and use the operating cycle label as the data set index to construct the charging and discharging data set of the vehicle battery corresponding to the operating cycle.

[0016] Optionally, the charging and discharging data of the vehicle battery corresponding to the operation cycle includes battery temperature data and charge consumption data;

[0017] The charging and discharging data set corresponding to the operation cycle of the vehicle battery is indexed by the corresponding operation cycle tag, and the charging and discharging data of the vehicle battery in the corresponding operation cycle is retrieved by searching the corresponding operation cycle tag.

[0018] Optionally, the battery status analysis module includes a periodic loss analysis unit and a curve model analysis unit;

[0019] The cycle loss analysis unit is electrically connected to the data integration processing unit and the curve model analysis unit respectively, and the cycle loss analysis unit is used to determine the actual battery discharge loss of the vehicle battery corresponding to the operation cycle according to the charge and discharge data set of the vehicle battery corresponding to the operation cycle;

[0020] The curve model analysis unit is electrically connected to the balanced charging planning module, and is used to obtain the predicted battery discharge loss of the vehicle battery corresponding to the operating cycle, and to construct a curve analysis model of the actual battery discharge loss and the predicted battery discharge loss of the vehicle battery corresponding to the operating cycle, so as to determine the comprehensive loss of the vehicle battery corresponding to the operating cycle.

[0021] Optionally, the periodic loss analysis unit includes a periodic loss analysis subunit;

[0022] The periodic loss analysis subunit is electrically connected to the data integration processing unit and the curve model analysis unit respectively, and the periodic loss analysis subunit is used to calculate the periodic loss according to the formula Determine the actual battery discharge loss value B(T) of the vehicle battery corresponding to the operation cycle n );

[0023] Among them, T n is the operating cycle corresponding to the vehicle battery, n is the number of operating cycles, t(T n ) is the time length of the corresponding operation cycle of the vehicle battery, W is the average battery temperature value during the corresponding operation cycle of the vehicle battery, LC is the battery charge consumption value during the corresponding operation cycle of the vehicle battery, α1, α2, β1 and β2 are fitting coefficients, and exp is an exponential function.

[0024] Optionally, the curve model analysis unit includes a predicted loss acquisition subunit, a curve model construction subunit, a battery loss analysis subunit and a battery loss determination subunit;

[0025] The predicted loss acquisition subunit is used to calculate the loss according to the formula R(Tn )=S(T n )×{1-exp[-k(T n )×t(T n )]}, determine the battery discharge prediction loss value R(T) of the vehicle battery corresponding to the operation cycle n ); where S(T n ) is the initial capacity of the battery corresponding to the operation cycle of the vehicle battery, k(T n ) is the average battery loss rate of the vehicle battery in the corresponding operating cycle;

[0026] The curve model construction subunit is electrically connected to the cycle loss analysis subunit, the predicted loss acquisition subunit, and the battery loss analysis subunit, respectively. The curve model construction subunit is used to perform plane coordinate mapping of the actual battery discharge loss value and the predicted battery discharge loss value at the continuous time points in the corresponding operation cycles, the horizontal axis is the continuous time point, and the vertical axis is the actual battery discharge loss value and the predicted battery discharge loss value, respectively. The actual battery discharge loss value corresponding to each of the operation cycles is connected by a smooth curve to construct a full-cycle battery actual loss curve, and the predicted battery discharge loss value corresponding to each of the operation cycles is connected by a smooth curve to construct a full-cycle battery predicted loss curve, so as to construct a curve analysis model of the actual battery discharge loss and the predicted battery discharge loss corresponding to the operation cycle of the vehicle battery;

[0027] The battery loss analysis subunit is electrically connected to the battery loss determination subunit, and the battery loss analysis subunit is used to calculate the battery loss according to the formula The real-time comprehensive consumption rate RCT of the vehicle battery corresponding to the operation cycle; wherein, Q B is the function corresponding to the actual battery consumption curve of the full cycle, ave(Q B ) is the average value on the actual battery consumption curve of the full cycle, Q Bmax is the maximum value on the actual battery consumption curve of the full cycle, Q Bmin is the minimum value on the actual battery consumption curve of the full cycle, Q Bh is the real-time consumption value of the vehicle battery corresponding to the operation cycle, Q R is the function corresponding to the full cycle battery prediction loss curve, ave(Q R ) is the average value on the full cycle battery prediction loss curve, Q Rmax is the maximum value on the predicted loss curve of the full cycle battery, Q Rmin The minimum value on the full cycle battery prediction wear curve;

[0028] The battery loss determination subunit is electrically connected to the balanced charging planning module, and the battery loss determination subunit is used to determine that the vehicle battery has abnormal loss when the real-time comprehensive loss rate RCT of the vehicle battery corresponding to the operating cycle is greater than or equal to the first preset loss rate threshold RCT(v); and to determine that the vehicle battery has normal loss when the real-time comprehensive loss rate RCT of the vehicle battery corresponding to the operating cycle is less than the first preset loss rate threshold RCT(v).

[0029] Optionally, the balanced charging planning module includes a health status analysis unit and a balanced charging planning unit;

[0030] The health status analysis unit is electrically connected to the battery loss determination subunit and the balanced charging planning unit respectively, and the health status analysis unit is used to calculate the battery loss determination subunit and the balanced charging planning unit according to the calculation formula. Determine the real-time health assessment value HV of the vehicle battery corresponding to the operating cycle; where t0 is the current time point, G(t0) is the real-time charge and discharge cycle number corresponding to the vehicle battery, G(t0∈T n ) is the operation cycle T to which the current time point t0 belongs n The corresponding predicted average number of charge and discharge cycles;

[0031] The balanced charging planning unit is used to formulate the balanced charging scheme for the corresponding operation cycle of the vehicle battery based on the battery health level division rule and the real-time health assessment value HV of the vehicle battery corresponding to the operation cycle.

[0032] Optionally, the balanced charging planning unit includes a health level division subunit and a balanced charging planning subunit;

[0033] The health level division subunit is used to determine the first-level health level division interval as [k×HV(max), HV(max)] and the second-level health level division interval as [HV(min), k×HV(max)) according to the predicted maximum health assessment value HV(max) of the vehicle battery corresponding to the operation cycle, the predicted minimum health assessment value HV(min) of the vehicle battery corresponding to the operation cycle, and the battery health level division coefficient k;

[0034] The balanced charging planning subunit is electrically connected to the health level division subunit and the health status analysis unit respectively, and the balanced charging planning subunit is used to formulate the balanced charging plan for the corresponding operating cycle of the vehicle battery according to the first-level health level division interval or the second-level health level division interval in which the real-time health assessment value HV of the vehicle battery corresponding to the operating cycle is located.

[0035] Optionally, the battery information feedback module includes a battery status feedback unit and a balanced charging planning feedback unit;

[0036] The battery status feedback unit is electrically connected to the battery status analysis module, and the battery status feedback unit is used to feedback and visually output the comprehensive loss of the vehicle battery corresponding to the operation cycle;

[0037] The balanced charging planning feedback unit is electrically connected to the balanced charging planning module, and the balanced charging planning feedback unit is used to feedback and visually output the balanced charging scheme planned corresponding to the vehicle battery.

[0038] In a second aspect, an embodiment of the present invention further provides an integrated new energy vehicle battery detection device with a balancing function, including an integrated new energy vehicle battery detection system with a balancing function as described in any one of the first aspects.

[0039] The embodiment of the present invention provides an integrated new energy vehicle battery detection system and device with a balancing function, the battery detection system includes a battery data monitoring module, a battery state analysis module, a balanced charging planning module and a battery information feedback module; the battery data monitoring module is used to monitor the charging and discharging data of the vehicle battery corresponding to the operating cycle under the vehicle operating state, and construct a charging and discharging data set of the vehicle battery corresponding to the operating cycle for cloud storage; the battery state analysis module is electrically connected to the battery data monitoring module and the balanced charging planning module respectively, the battery state analysis module is used to analyze the charging and discharging data set of the vehicle battery, and in combination with the battery discharge prediction loss of the vehicle battery corresponding to the operating cycle, construct a curve analysis model to analyze the comprehensive loss of the vehicle battery corresponding to the operating cycle; the balanced charging planning module is used to evaluate the battery health state of the vehicle battery corresponding to the operating cycle based on the comprehensive loss of the vehicle battery corresponding to the operating cycle, and plan the corresponding balanced charging plan; the battery information feedback module is electrically connected to the battery state analysis module and the balanced charging planning module respectively, the battery information feedback module is used to feedback and output the comprehensive loss of the vehicle battery corresponding to the operating cycle, and the corresponding planned balanced charging plan;

[0040] Based on data synchronization between the inspection platform and the user's mobile terminal, users can display vehicle inspection reports and query historical inspection reports on the mobile terminal; the vehicle inspection report indicators include:

[0041] Safety indicators: maximum cell voltage, maximum cell temperature, battery voltage difference, battery temperature difference, battery consistency, etc.

[0042] Accuracy indicators: BMS voltage measurement accuracy, BMS current measurement accuracy, SOC accuracy, SOC linearity, etc.;

[0043] Capacity indicators: battery health SOH, internal resistance growth rate, battery consistency, etc.;

[0044] Efficiency indicators: real-time charging and discharging power, demand current deviation, demand voltage deviation, etc.;

[0045] Based on the health data of the power battery and the vehicle, a comprehensive assessment is made on the vehicle's valuation, taking into account the vehicle brand, age, mileage, market conditions and vehicle depreciation rate.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The battery detection system realizes full-cycle usage status detection of new energy vehicle batteries; obtains the battery wear status in different cycles through multi-segment analysis of the battery usage cycle, and builds a curve analysis model in combination with the factory predicted wear analysis of the battery to calculate the full-cycle battery wear rate of the vehicle battery; evaluates the real-time health status value of the battery in combination with the battery wear rate, and outputs a corresponding balanced charging plan for the corresponding level of the real-time status value of the battery; the present invention detects the multi-cycle usage status data of the vehicle battery and conducts a comprehensive evaluation of the full-cycle battery wear, performs real-time health analysis based on battery wear, and outputs a balanced charging plan for the corresponding level, which effectively improves the real-time grasp of the battery status by the vehicle user and greatly improves the safety observation efficiency of the battery; and effectively improves the charging plan of batteries in different states and enhances the intelligence of battery charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0049] Figure 1 It is a structural schematic diagram of an integrated new energy vehicle battery detection system with a balancing function provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0051] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. It should be noted that the directional words such as "upper", "lower", "left", "right" and the like described in the embodiments of the present invention are described at the angles shown in the accompanying drawings and should not be understood as limitations on the embodiments of the present invention. In addition, in the context, it is also necessary to understand that when it is mentioned that an element is formed "on" or "under" another element, it can not only be directly formed "on" or "under" another element, but also indirectly formed "on" or "under" another element through an intermediate element. The terms "first", "second", etc. are only used for descriptive purposes and do not represent any order, quantity or importance, but are only used to distinguish different components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood in specific circumstances.

[0052] The term “including” and its variations used in the present invention are open inclusions, that is, “including but not limited to.” The term “based on” means “based at least in part on.” The term “one embodiment” means “at least one embodiment.”

[0053] It should be noted that the concepts such as "first" and "second" mentioned in the present invention are only used to distinguish the corresponding contents, and are not used to limit the order or interdependence.

[0054] Figure 1 is a schematic diagram of the structure of an integrated new energy vehicle battery detection system with a balancing function provided by an embodiment of the present invention. Figure 1 As shown, the battery detection system includes a battery data monitoring module, a battery status analysis module, a balanced charging planning module and a battery information feedback module; the battery data monitoring module is used to monitor the charging and discharging data of the vehicle battery corresponding to the operating cycle under the vehicle operating state, and construct a charging and discharging data set of the vehicle battery corresponding to the operating cycle for cloud storage; the battery status analysis module is electrically connected to the battery data monitoring module and the balanced charging planning module respectively, and the battery status analysis module is used to analyze the charging and discharging data set of the vehicle battery, and build a curve analysis model to analyze the comprehensive loss of the vehicle battery corresponding to the operating cycle in combination with the battery discharge prediction loss of the vehicle battery corresponding to the operating cycle; the balanced charging planning module is used to evaluate the battery health status of the vehicle battery corresponding to the operating cycle based on the comprehensive loss of the vehicle battery corresponding to the operating cycle, and plan the corresponding balanced charging plan; the battery information feedback module is electrically connected to the battery status analysis module and the balanced charging planning module respectively, and the battery information feedback module is used to feedback and output the comprehensive loss of the vehicle battery corresponding to the operating cycle, and the corresponding planned balanced charging plan.

[0055] Specifically, the battery detection system uses an on-board sensor device to monitor the periodic charge and discharge data of the vehicle battery under the vehicle operation state, and constructs a corresponding operation cycle battery charge and discharge data set for cloud storage; analyzes the battery discharge loss status of the vehicle in each operation cycle based on the periodic battery charge and discharge data set; constructs a curve model to analyze the comprehensive loss of the current vehicle battery by combining the vehicle battery prediction periodic loss data with the current vehicle battery discharge set data of each operation cycle; comprehensively evaluates the health status of the vehicle battery based on the comprehensive loss of the current vehicle battery, and plans a balanced charging plan based on the evaluation results; backs up the periodic loss analysis data of the vehicle battery, and provides feedback on the health status of the vehicle battery and outputs a balanced charging plan.

[0056] Optionally, continue to refer to Figure 1 The battery data monitoring module includes a battery data acquisition unit and a data integration processing unit; the battery data acquisition unit is used to monitor the charging and discharging data of the vehicle battery corresponding to the operating cycle under the vehicle operating state, and store the data in the cloud through cloud transmission; the data integration processing unit is electrically connected to the battery data acquisition unit and the battery status analysis module respectively, and the data integration processing unit is used to integrate the charging and discharging data of the vehicle battery corresponding to the operating cycle based on the operating cycle label, and use the operating cycle label as the data set index to construct the charging and discharging data set of the vehicle battery corresponding to the operating cycle.

[0057] Specifically, the battery detection system monitors and collects the battery's periodic charge and discharge data through an on-board battery monitoring sensor device and transmits it to the cloud for cloud storage; integrates the collected data based on the collection cycle label; uses the collection cycle label as the integrated data set index, and constructs a battery periodic charge and discharge data set based on the set index.

[0058] Optionally, continue to refer to Figure 1 The charging and discharging data of the vehicle battery corresponding to the operating cycle include battery temperature data and charge consumption data; the charging and discharging data set of the vehicle battery corresponding to the operating cycle is indexed by the corresponding operating cycle tag, and the charging and discharging data of the vehicle battery corresponding to the operating cycle is retrieved by searching the corresponding operating cycle tag.

[0059] Specifically, the battery cycle charge and discharge data set of the battery detection system uses the corresponding collection cycle tag as the set identity index, and the vehicle battery charge and discharge data under the corresponding cycle is retrieved by retrieving the cycle tag.

[0060] Optionally, continue to refer to Figure 1The battery status analysis module includes a cycle loss analysis unit and a curve model analysis unit; the cycle loss analysis unit is electrically connected to the data integration processing unit and the curve model analysis unit respectively, and the cycle loss analysis unit is used to determine the actual battery discharge loss of the vehicle battery corresponding to the operating cycle according to the charging and discharging data set of the vehicle battery corresponding to the operating cycle; the curve model analysis unit is electrically connected to the balanced charging planning module, and the curve model analysis unit is used to obtain the predicted battery discharge loss of the vehicle battery corresponding to the operating cycle, and construct a curve analysis model of the actual battery discharge loss and the predicted battery discharge loss of the vehicle battery corresponding to the operating cycle, so as to determine the comprehensive loss of the vehicle battery corresponding to the operating cycle.

[0061] Specifically, the battery detection system retrieves the charge and discharge data of the corresponding cycle by retrieving the historical cycle label index of the current vehicle battery; and analyzes the battery consumption of the corresponding cycle based on the charge and discharge data of the battery in each cycle; analyzes the predicted consumption of each cycle of the current vehicle battery; constructs a curve analysis model by combining the actual battery consumption of each cycle of the current battery with the predicted consumption, and analyzes the real-time comprehensive consumption of the current vehicle battery based on the curve analysis model.

[0062] Optionally, continue to refer to Figure 1 The periodic loss analysis unit includes a periodic loss analysis subunit; the periodic loss analysis subunit is electrically connected to the data integration processing unit and the curve model analysis unit respectively, and the periodic loss analysis subunit is used to calculate the periodic loss according to the formula Determine the actual battery discharge loss value B(T n ), where T n is the operating cycle corresponding to the vehicle battery, n is the number of operating cycles, t(T n ) is the time length of the corresponding operation cycle of the vehicle battery, W is the average battery temperature value during the corresponding operation cycle of the vehicle battery, LC is the battery charge consumption value during the corresponding operation cycle of the vehicle battery, α1, α2, β1 and β2 are fitting coefficients, and exp is an exponential function.

[0063] Specifically, the battery detection system retrieves the charge and discharge data set of the corresponding battery up to the current cycle based on the cloud storage space of the current battery; the calculation formula for performing battery consumption analysis on each operation cycle based on each cycle label is B(T n ) corresponding formula.

[0064] Optionally, continue to refer to Figure 1 The curve model analysis unit includes a predicted loss acquisition subunit, a curve model construction subunit, a battery loss analysis subunit and a battery loss determination subunit; the predicted loss acquisition subunit is used to calculate the battery loss according to the formula R(Tn )=S(T n )×{1-exp[-k(T n )×t(T n )]}, determine the battery discharge prediction loss value R(T n ); where S(T n ) is the initial capacity of the vehicle battery corresponding to the operating cycle, k(T n ) is the average battery loss rate in the corresponding operating cycle of the vehicle battery; the curve model construction subunit is electrically connected to the cycle loss analysis subunit, the predicted loss acquisition subunit, and the battery loss analysis subunit respectively, and the curve model construction subunit is used to map the actual battery discharge loss value and the predicted battery discharge loss value at continuous time points in each corresponding operating cycle to the plane coordinate, the horizontal axis is the continuous time point, and the vertical axis is the actual battery discharge loss value and the predicted battery discharge loss value respectively, and the actual battery discharge loss value corresponding to each operating cycle is connected by a smooth curve to construct a full-cycle battery actual loss curve, and the predicted battery discharge loss value corresponding to each operating cycle is connected by a smooth curve to construct a full-cycle battery predicted loss curve, so as to construct a curve analysis model of the actual battery discharge loss and the predicted battery discharge loss of the vehicle battery corresponding to the operating cycle; the battery loss analysis subunit is electrically connected to the battery loss determination subunit, and the battery loss analysis subunit is used to calculate the actual battery discharge loss according to the calculation formula The real-time comprehensive consumption rate RCT of the vehicle battery corresponding to the operation cycle; among them, Q B is the function corresponding to the actual battery consumption curve of the full cycle, ave(Q B ) is the average value of the actual battery consumption curve over the entire cycle, Q Bmax is the maximum value of the actual battery consumption curve in the full cycle, Q Bmin is the minimum value on the actual battery consumption curve of the full cycle, Q Bh is the real-time consumption value of the vehicle battery corresponding to the operation cycle, Q R is the function corresponding to the full cycle battery prediction loss curve, ave(Q R ) is the average value of the predicted battery loss curve for the entire cycle, Q Rmax Q is the maximum value on the full cycle battery prediction loss curve. Rmin It is the minimum value on the full-cycle battery prediction loss curve; the battery loss determination subunit is electrically connected to the balanced charging planning module, and the battery loss determination subunit is used to determine that the vehicle battery has abnormal loss when the real-time comprehensive loss rate RCT of the vehicle battery corresponding to the operating cycle is greater than or equal to the first preset loss rate threshold RCT(v); when the real-time comprehensive loss rate RCT of the vehicle battery corresponding to the operating cycle is less than the first preset loss rate threshold RCT(v), determine that the vehicle battery has normal loss.

[0065] Specifically, the battery detection system calculates the corresponding cycle analysis of the vehicle battery's factory predicted battery consumption using the formula R(T n ) corresponding formula. The battery detection system also constructs a curve analysis model based on the actual loss and predicted loss of the corresponding vehicle battery in the corresponding cycle; the actual loss value and predicted loss value of the battery at continuous time points in each cycle are mapped to plane coordinates, and the actual loss coordinates and predicted loss coordinates are constructed with the cycle time point as the horizontal coordinate and the loss value at the corresponding time point as the vertical coordinate; according to the mapped actual loss coordinates and predicted loss coordinates of each cycle, the actual loss coordinate points and predicted loss coordinate points of each cycle are connected by smooth curves to construct the actual loss curve of the full cycle battery and the predicted loss curve of the full cycle battery. The calculation formula for analyzing the real-time comprehensive loss of the current vehicle battery in combination with the actual loss curve of the full cycle battery and the predicted loss curve of the full cycle battery is the corresponding formula of RCT. Based on the real-time comprehensive consumption analysis results of the vehicle battery, by introducing the factory consumption rate comparison value RCT(v) of the vehicle battery, if the real-time comprehensive consumption rate of the current vehicle battery RCT≥RCT(v), the current vehicle battery is marked as abnormal consumption; if the real-time comprehensive consumption rate of the current vehicle battery is 0<RCT<RCT(v), the current vehicle battery is marked as normal consumption.

[0066] Optionally, continue to refer to Figure 1 The balanced charging planning module includes a health status analysis unit and a balanced charging planning unit; the health status analysis unit is electrically connected to the battery loss determination subunit and the balanced charging planning unit respectively, and the health status analysis unit is used to calculate the battery loss determination subunit and the balanced charging planning unit according to the calculation formula. Determine the real-time health assessment value HV of the vehicle battery corresponding to the operating cycle; where t0 is the current time point, G(t0) is the real-time charge and discharge cycle number corresponding to the vehicle battery, G(t0∈T n ) is the operation cycle T to which the current time point t0 belongs n The corresponding predicted average number of charge and discharge cycles; the balanced charging planning unit is used to formulate a balanced charging plan for the vehicle battery corresponding to the operating cycle based on the battery health level classification rules and the real-time health assessment value HV of the vehicle battery corresponding to the operating cycle.

[0067] Specifically, the battery detection system comprehensively evaluates the real-time health status of the vehicle battery in combination with the real-time consumption of the vehicle battery; the calculation formula for the real-time health status evaluation of the vehicle battery based on the health consumption status is the HV corresponding formula. The battery detection system also divides the vehicle into health levels according to the real-time health status evaluation value of the vehicle battery, and performs balanced charging planning based on the real-time health level of the vehicle battery.

[0068] Optionally, continue to refer to Figure 1 The balanced charging planning unit includes a health level division subunit and a balanced charging planning subunit; the health level division subunit is used to determine the first-level health level division interval as [k×HV(max), HV(max)] and the second-level health level division interval as [HV(min), k×HV(max)) according to the predicted maximum health assessment value HV(max) of the vehicle battery corresponding to the operating cycle, the predicted minimum health assessment value HV(min) of the vehicle battery corresponding to the operating cycle and the battery health level division coefficient k; the balanced charging planning subunit is electrically connected to the health level division subunit and the health status analysis unit respectively, and the balanced charging planning subunit is used to formulate a balanced charging plan for the vehicle battery corresponding to the operating cycle according to the first-level health level division interval or the second-level health level division interval where the real-time health assessment value HV of the vehicle battery corresponding to the operating cycle is located.

[0069] Specifically, the battery detection system divides the battery health level by combining the predicted health value of the vehicle battery before leaving the factory, and calculates the battery health level division threshold by proposing a division coefficient, and the calculation formula is HV(th)=k×HV(max); wherein HV(th) is the battery health level division threshold; HV(max) is the maximum health assessment value predicted before leaving the factory; and k is the battery health level division coefficient. The battery health level interval is constructed based on the battery health level division threshold, with [HV(th), HV(max)] as the first-level health level interval; and [HV(min), HV(th)) as the second-level health level interval. According to the level interval of the current real-time vehicle battery health assessment value, the battery equalization charging parameters of the corresponding interval are retrieved and the corresponding equalization charging plan is formulated. And, if the current vehicle battery health assessment value HV<HV(min), the vehicle battery is marked with an abnormal health state, wherein HV(min) is the minimum allowable health value of the vehicle battery.

[0070] Optionally, continue to refer to Figure 1 The battery information feedback module includes a battery status feedback unit and a balanced charging planning feedback unit; the battery status feedback unit is electrically connected to the battery status analysis module, and the battery status feedback unit is used to feedback and visualize the comprehensive loss of the vehicle battery corresponding to the operating cycle; the balanced charging planning feedback unit is electrically connected to the balanced charging planning module, and the balanced charging planning feedback unit is used to feedback and visualize the balanced charging plan corresponding to the vehicle battery.

[0071] Specifically, the battery detection system visualizes the real-time consumption data and health status data of the vehicle battery and warns of abnormal conditions; and, when the vehicle battery needs to be charged, it outputs a balanced charging plan based on the current health status of the vehicle battery.

[0072] Based on the same inventive concept, the embodiment of the present invention also provides an integrated new energy vehicle battery detection device with a balancing function, and the battery detection device includes an integrated new energy vehicle battery detection system with a balancing function as provided in any one of the embodiments of the present invention. Therefore, the integrated new energy vehicle battery detection device with a balancing function provided in the embodiment of the present invention has the corresponding beneficial effects of the integrated new energy vehicle battery detection system with a balancing function provided in the embodiment of the present invention, which will not be repeated here.

[0073] In a specific embodiment, for a new energy vehicle battery detection device equipped with an integrated new energy vehicle battery detection system with a balancing function of the present invention, it monitors and collects the battery's periodic charge and discharge data through an on-board battery monitoring sensor device and transmits it to the cloud for cloud storage, and integrates the collected data based on the collection cycle label. The collection cycle label is used as the integrated data set index, and a battery cycle charge and discharge data set based on the set index is constructed, wherein the cycle charge and discharge data is the battery discharge temperature data and the charge consumption data. The battery cycle charge and discharge data set is based on the corresponding collection cycle label as the set identity index, and the vehicle battery charge and discharge data under the corresponding cycle is retrieved by retrieving the cycle label.

[0074] By retrieving the historical cycle tag index of the current vehicle battery, the charge and discharge data of the corresponding cycle are retrieved, and the battery consumption of the corresponding cycle is analyzed based on the charge and discharge data of the battery in each cycle. Based on the cloud storage space of the current battery, the charge and discharge data set of the corresponding battery up to the current cycle is retrieved.

[0075] Among them, the battery consumption analysis of each operation cycle is performed based on each cycle label, and the calculation formula is: Among them, B(T n ) is the actual battery discharge loss value of the vehicle battery corresponding to the operating cycle, T n is the operating cycle corresponding to the vehicle battery, n is the number of operating cycles, t(T n ) is the time length of the corresponding operation cycle of the vehicle battery, W is the average battery temperature value during the corresponding operation cycle of the vehicle battery, LC is the battery charge consumption value during the corresponding operation cycle of the vehicle battery, α1, α2, β1 and β2 are fitting coefficients, and exp is an exponential function.

[0076] By analyzing the predicted consumption of each cycle of the current vehicle battery, a curve analysis model is constructed by combining the actual battery consumption of each cycle with the predicted consumption, and the real-time comprehensive consumption of the current vehicle battery is analyzed based on the curve analysis model.

[0077] Among them, the corresponding cycle analysis is performed on the factory predicted battery consumption of the vehicle battery, and the analysis calculation is R(Tn )=S(T n )×{1-exp[-k(T n )×t(T n )]}, where R(T n ) is the predicted battery discharge loss value of the vehicle battery corresponding to the operating cycle, S(T n ) is the initial capacity of the vehicle battery corresponding to the operating cycle, k(T n ) is the average battery loss rate during the corresponding operating cycle of the vehicle battery.

[0078] A curve analysis model is constructed based on the actual loss and predicted loss of the battery of the corresponding vehicle in the corresponding cycle. The actual loss value and predicted loss value of the battery at continuous time points in each cycle are mapped into plane coordinates. The actual loss coordinate and predicted loss coordinate are constructed with the cycle time point as the horizontal coordinate and the loss value at the corresponding time point as the vertical coordinate. According to the mapped actual loss coordinates and predicted loss coordinates of each cycle, the actual loss coordinate points and the predicted loss coordinate points of each cycle are connected by smooth curves to construct the actual loss curve of the battery throughout the cycle and the predicted loss curve of the battery throughout the cycle.

[0079] Among them, the real-time comprehensive consumption of the current vehicle battery is analyzed by combining the full-cycle battery actual consumption curve and the full-cycle battery predicted consumption curve. The calculation formula is: Among them, RCT is the real-time comprehensive consumption rate of the vehicle battery corresponding to the operation cycle, Q B is the function corresponding to the actual battery consumption curve of the full cycle, ave(Q B ) is the average value of the actual battery consumption curve over the entire cycle, Q Bmax is the maximum value of the actual battery consumption curve in the full cycle, Q Bmin is the minimum value on the actual battery consumption curve of the full cycle, Q Bh is the real-time consumption value of the vehicle battery corresponding to the operation cycle, Q R is the function corresponding to the full cycle battery prediction loss curve, ave(Q R ) is the average value of the predicted battery loss curve for the entire cycle, Q Rmax Q is the maximum value on the full cycle battery prediction loss curve. Rmin Predict the minimum value on the wear curve for a full cycle battery.

[0080] Based on the real-time comprehensive consumption analysis results of the vehicle battery, by introducing the factory consumption rate comparison value RCT(v) of the vehicle battery, if the real-time comprehensive consumption rate of the current vehicle battery RCT≥RCT(v), the current vehicle battery is marked as abnormal consumption; if the real-time comprehensive consumption rate of the current vehicle battery is 0<RCT<RCT(v), the current vehicle battery is marked as normal consumption.

[0081] Combined with the real-time consumption of the vehicle battery, the real-time health status of the vehicle battery is comprehensively evaluated. Among them, the real-time health status evaluation of the vehicle battery based on the health consumption status is calculated as follows: Where HV is the real-time health assessment value of the vehicle battery corresponding to the operating cycle, t0 is the current time point, G(t0) is the real-time charge and discharge cycle number corresponding to the vehicle battery, G(t0∈T n ) is the operation cycle T to which the current time point t0 belongs n The corresponding predicted average number of charge and discharge cycles.

[0082] The vehicle is divided into health levels according to the real-time health status assessment value of the vehicle battery, and balanced charging planning is performed based on the real-time health level of the vehicle battery. The battery health level is divided by combining the predicted health value of the vehicle battery before leaving the factory, and the battery health level division threshold is calculated by proposing a division coefficient. The calculation formula is HV(th)=k×HV(max); where HV(th) is the battery health level division threshold; HV(max) is the maximum health assessment value predicted before leaving the factory; and k is the battery health level division coefficient. The battery health level interval is constructed based on the battery health level division threshold, with [HV(th), HV(max)] as the first-level health level interval; and [HV(min), HV(th)) as the second-level health level interval. According to the level interval where the health assessment value of the current real-time vehicle battery is located, the battery balanced charging parameters of the corresponding interval are retrieved and the corresponding balanced charging plan is formulated. And, if the current health assessment value HV of the vehicle battery is less than HV(min), the vehicle battery is marked as having an abnormal health status, where HV(min) is the minimum allowable health value of the vehicle battery.

[0083] The real-time consumption data and health status data of the vehicle battery are visualized and output, and abnormal status is warned; and when the vehicle battery needs to be charged, a balanced charging plan is output based on the current health status of the vehicle battery.

[0084] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, combinations and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. An integrated new energy vehicle battery detection system with equalization function, characterized in that: Including battery data monitoring module, battery status analysis module, balanced charging planning module and battery information feedback module; The battery data monitoring module is used to monitor the charge and discharge data of the vehicle battery corresponding to the operation cycle under the vehicle operation state, and construct a charge and discharge data set of the vehicle battery corresponding to the operation cycle for cloud storage; The battery status analysis module is electrically connected to the battery data monitoring module and the balanced charging planning module respectively, and is used to analyze the charging and discharging data set of the vehicle battery, and to construct a curve analysis model to analyze the comprehensive loss of the vehicle battery in the corresponding operation cycle in combination with the battery discharge prediction loss of the vehicle battery; The balanced charging planning module is used to evaluate the battery health status of the vehicle battery in the corresponding operation cycle based on the comprehensive loss of the vehicle battery in the corresponding operation cycle, and plan a corresponding balanced charging plan; The battery information feedback module is electrically connected to the battery status analysis module and the balanced charging planning module respectively, and is used to feed back and output the comprehensive loss situation of the vehicle battery corresponding to the operation cycle, and the corresponding planned balanced charging plan.

2. The battery detection system according to claim 1, characterized in that: The battery data monitoring module includes a battery data acquisition unit and a data integration processing unit; The battery data acquisition unit is used to monitor the charge and discharge data of the vehicle battery corresponding to the operation cycle under the vehicle operation state, and store the data in the cloud through cloud transmission; The data integration processing unit is electrically connected to the battery data acquisition unit and the battery status analysis module respectively. The data integration processing unit is used to integrate the charging and discharging data of the vehicle battery corresponding to the operating cycle based on the operating cycle label, and use the operating cycle label as the data set index to construct the charging and discharging data set of the vehicle battery corresponding to the operating cycle.

3. The battery detection system according to claim 2, characterized in that: The charging and discharging data of the vehicle battery corresponding to the operation cycle includes battery temperature data and charge consumption data; The charging and discharging data set corresponding to the operation cycle of the vehicle battery is indexed by the corresponding operation cycle tag, and the charging and discharging data of the vehicle battery in the corresponding operation cycle is retrieved by searching the corresponding operation cycle tag.

4. The battery detection system according to claim 3, characterized in that: The battery status analysis module includes a periodic loss analysis unit and a curve model analysis unit; The cycle loss analysis unit is electrically connected to the data integration processing unit and the curve model analysis unit respectively, and the cycle loss analysis unit is used to determine the actual battery discharge loss of the vehicle battery corresponding to the operation cycle according to the charge and discharge data set of the vehicle battery corresponding to the operation cycle; The curve model analysis unit is electrically connected to the balanced charging planning module, and is used to obtain the predicted battery discharge loss of the vehicle battery corresponding to the operating cycle, and to construct a curve analysis model of the actual battery discharge loss and the predicted battery discharge loss of the vehicle battery corresponding to the operating cycle, so as to determine the comprehensive loss of the vehicle battery corresponding to the operating cycle.

5. The battery detection system according to claim 4, characterized in that: The periodic loss analysis unit includes a periodic loss analysis subunit; The periodic loss analysis subunit is electrically connected to the data integration processing unit and the curve model analysis unit respectively, and the periodic loss analysis subunit is used to calculate the periodic loss according to the formula Determine the actual battery discharge loss value B(T) of the vehicle battery corresponding to the operation cycle n ); Among them, T n is the operating cycle corresponding to the vehicle battery, n is the number of operating cycles, t(T n ) is the time length of the corresponding operation cycle of the vehicle battery, W is the average battery temperature value during the corresponding operation cycle of the vehicle battery, LC is the battery charge consumption value during the corresponding operation cycle of the vehicle battery, α1, α2, β1 and β2 are fitting coefficients, and exp is an exponential function.

6. The battery detection system according to claim 5, characterized in that: The curve model analysis unit includes a predicted loss acquisition subunit, a curve model construction subunit, a battery loss analysis subunit and a battery loss determination subunit; The predicted loss acquisition subunit is used to calculate the loss according to the formula R(T n )=S(T n )×{1-exp[-k(T n )×t(T n )]}, determine the battery discharge prediction loss value R(T) of the vehicle battery corresponding to the operation cycle n ); where S(T n ) is the initial capacity of the battery corresponding to the operation cycle of the vehicle battery, k(T n ) is the average battery loss rate of the vehicle battery in the corresponding operating cycle; The curve model construction subunit is electrically connected to the cycle loss analysis subunit, the predicted loss acquisition subunit, and the battery loss analysis subunit, respectively. The curve model construction subunit is used to perform plane coordinate mapping of the actual battery discharge loss value and the predicted battery discharge loss value at the continuous time points in the corresponding operation cycles, the horizontal axis is the continuous time point, and the vertical axis is the actual battery discharge loss value and the predicted battery discharge loss value, respectively. The actual battery discharge loss value corresponding to each of the operation cycles is connected by a smooth curve to construct a full-cycle battery actual loss curve, and the predicted battery discharge loss value corresponding to each of the operation cycles is connected by a smooth curve to construct a full-cycle battery predicted loss curve, so as to construct a curve analysis model of the actual battery discharge loss and the predicted battery discharge loss corresponding to the operation cycle of the vehicle battery; The battery loss analysis subunit is electrically connected to the battery loss determination subunit, and the battery loss analysis subunit is used to calculate the battery loss according to the formula The real-time comprehensive consumption rate RCT of the vehicle battery corresponding to the operation cycle; wherein, Q B is the function corresponding to the actual battery consumption curve of the full cycle, ave(Q B ) is the average value on the actual battery consumption curve of the full cycle, Q Bmax is the maximum value on the actual battery consumption curve of the full cycle, Q Bmin is the minimum value on the actual battery consumption curve of the full cycle, Q Bh is the real-time consumption value of the vehicle battery corresponding to the operation cycle, Q R is the function corresponding to the full cycle battery prediction loss curve, ave(Q R ) is the average value on the full cycle battery prediction loss curve, Q Rmax is the maximum value on the predicted loss curve of the full cycle battery, Q Rmin The minimum value on the full cycle battery prediction wear curve; The battery loss determination subunit is electrically connected to the balanced charging planning module, and the battery loss determination subunit is used to determine that the vehicle battery has abnormal loss when the real-time comprehensive loss rate RCT of the vehicle battery corresponding to the operating cycle is greater than or equal to the first preset loss rate threshold RCT(v); and to determine that the vehicle battery has normal loss when the real-time comprehensive loss rate RCT of the vehicle battery corresponding to the operating cycle is less than the first preset loss rate threshold RCT(v).

7. The battery detection system according to claim 6, characterized in that: The balanced charging planning module includes a health status analysis unit and a balanced charging planning unit; The health status analysis unit is electrically connected to the battery loss determination subunit and the balanced charging planning unit respectively, and the health status analysis unit is used to calculate the battery loss determination subunit and the balanced charging planning unit according to the calculation formula. Determine the real-time health assessment value HV of the vehicle battery corresponding to the operating cycle; where t0 is the current time point, G(t0) is the real-time charge and discharge cycle number corresponding to the vehicle battery, G(t0∈T n ) is the operation cycle T to which the current time point t0 belongs n The corresponding predicted average number of charge and discharge cycles; The balanced charging planning unit is used to formulate the balanced charging scheme for the corresponding operation cycle of the vehicle battery based on the battery health level division rule and the real-time health assessment value HV of the vehicle battery corresponding to the operation cycle.

8. The battery detection system according to claim 7, characterized in that: The balanced charging planning unit includes a health level division subunit and a balanced charging planning subunit; The health level division subunit is used to determine the first-level health level division interval as [k×HV(max), HV(max)] and the second-level health level division interval as [HV(min), k×HV(max)) according to the predicted maximum health assessment value HV(max) of the vehicle battery corresponding to the operation cycle, the predicted minimum health assessment value HV(min) of the vehicle battery corresponding to the operation cycle, and the battery health level division coefficient k; The balanced charging planning subunit is electrically connected to the health level division subunit and the health status analysis unit respectively, and the balanced charging planning subunit is used to formulate the balanced charging plan for the corresponding operating cycle of the vehicle battery according to the first-level health level division interval or the second-level health level division interval in which the real-time health assessment value HV of the vehicle battery corresponding to the operating cycle is located.

9. The battery detection system according to claim 1, characterized in that: The battery information feedback module includes a battery status feedback unit and a balanced charging planning feedback unit; The battery status feedback unit is electrically connected to the battery status analysis module, and the battery status feedback unit is used to feedback and visually output the comprehensive loss of the vehicle battery corresponding to the operation cycle; The balanced charging planning feedback unit is electrically connected to the balanced charging planning module, and the balanced charging planning feedback unit is used to feedback and visually output the balanced charging scheme planned corresponding to the vehicle battery.

10. An integrated new energy vehicle battery detection device with equalization function, characterized in that: It comprises an integrated new energy vehicle battery detection system with a balancing function as described in any one of claims 1 to 9.

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