Computer-implemented method for determining a predicted temperature profile of an electrical storage device, vehicle, and system.

Abstract

A computer-implemented method (100) for determining a predicted temperature profile of an electrical storage device (12) of a vehicle (10) in a passive operating state, comprising at least one temperature sensor (14) for providing at least one temperature signal indicating a current temperature of the electrical storage device (12), and at least one further sensor (16-20) for providing at least one further sensor signal indicating data for deriving a location situation of the vehicle (10), wherein the at least one further sensor (16-20) is configured to determine at least a time and / or a mobile network reception quality, wherein the method (100) comprises at least the following steps: a. Receiving (102) the at least one temperature signal and the at least one other sensor signal; b. Determining (104) the location of the vehicle (10) from the received additional sensor signal; c. Determine (106) at least one influencing factor for the temperature of the electrical storage (12) taking into account the site conditions and the current temperature; and d. Determining (108) a predictive trend of the temperature of the electrical storage (12) based on the determined influencing factors and starting from the current temperature.

Description

[0001] The invention relates to a computer-implemented method for determining a predictive trend of the temperature of an electrical storage device, a vehicle and a system.

[0002] The performance characteristics of electrical storage devices can be represented, for example, by their state of charge, ranging from 0% to 100%. These characteristics are highly dependent on the temperature of the electrical storage device. Performance characteristics deteriorate at temperatures that are too high or too low compared to the optimal operating temperature range. For instance, if the electrical storage device is located in an electric vehicle and the vehicle is parked at low temperatures around -10°C, the displayed performance characteristics may have changed at a later time compared to when it was parked.

[0003] From WO 2023 / 157 278 A1, a device for estimating battery state is known, comprising a vehicle data acquisition unit, a temperature data acquisition unit, and an estimation unit. The vehicle data acquisition unit acquires vehicle stopping position information and battery information. The vehicle stopping position information indicates the stopping position of a vehicle equipped with a battery. The battery information indicates the state of the battery at the position where the vehicle stopped. The temperature data acquisition unit acquires temperature data relating to the temperature at the vehicle stopping position by using the vehicle stopping position information. The estimation unit estimates the state of the battery after the vehicle has stopped, using the battery information and the temperature data.

[0004] From DE 10 2020 202 983 A1, a method for operating a motor vehicle with a cooling system for cooling a traction battery is further disclosed, comprising the following steps: reading in travel data representative of a planned route, reading in operating parameters of the traction battery, evaluating the travel data and the operating parameters to determine a data set representative of a predicted temperature profile of the battery temperature, evaluating the data set for the predicted temperature profile of the battery temperature to determine a phase of particularly high cooling power demand during the route, intermediate storage of cooling energy during the driving of the planned route by utilizing the heat storage capacities of the traction battery before the phase of particularly high cooling power demand for provision during the phase of high cooling power, if a phase of particularly high cooling power demand has been determined during the route.where a required battery temperature is determined, to which the traction battery is cooled before the phase.

[0005] DE 10 2020 216 548 A1 relates to a method for operating a motor vehicle, wherein the motor vehicle can be operated according to an operating mode that depends on a meteorological forecast, wherein a plurality of recording units record meteorological measurement data, the recorded meteorological measurement data are transmitted to a central evaluation unit, the central evaluation unit creates a meteorological map based on the recorded meteorological measurement data, a local meteorological forecast for the motor vehicle is determined based on the meteorological map and the motor vehicle is operated based on the local meteorological forecast.

[0006] German patent DE 10 2020 115 896 A1 discloses a method and an assistance system for thermal management in a motor vehicle, as well as a corresponding motor vehicle. The method generates a forecast for energy consumption and the resulting future temperature behavior based on the vehicle's operating strategy. Based on this forecast, the operating strategy is evaluated with respect to at least one predefined criterion. Depending on the evaluation, the operating strategy is then modified to achieve an improved rating with respect to the criterion. The motor vehicle is then controlled according to this modified operating strategy.

[0007] The object of the invention is to provide a computer-implemented method that provides an improved estimation of the performance characteristics of the electrical storage device.

[0008] The problem is solved by the features of the independent claims. Advantageous further developments are the subject of the dependent claims and the following description.

[0009] According to a first aspect, a computer-implemented method for determining a predictive temperature profile of an electrical storage device of a vehicle in a passive operating state is described, comprising at least one temperature sensor for providing at least one temperature signal indicating the current temperature of the electrical storage device, and at least one further sensor for providing at least one additional sensor signal indicating data for deriving a location status of the vehicle, wherein the at least one additional sensor is configured to determine at least a time and / or a mobile network reception quality, wherein the method comprises at least the following steps: receiving the at least one temperature signal and the at least one additional sensor signal; determining a location status of the vehicle from the received additional sensor signal;Determine at least one influencing factor for the temperature of the electrical storage system, taking into account the location and the current temperature; and determine a forecast of the temperature of the electrical storage system based on the determined influencing factors and starting from the current temperature.

[0010] This computer-implemented method provides a forecast for the temperature profile of a vehicle's electrical storage system during passive operation. The vehicle's location is taken into account when generating this forecast. Based on the predicted temperature profile of the electrical storage system, its future performance characteristics, such as its state of charge, can be inferred. A passive operating state refers to a non-driving state of the vehicle. The vehicle can be in a passive operating state when it is stationary or parked. Data from the additional sensor signal allows conclusions to be drawn about the vehicle's location. Depending on the specific conditions of the location in which the vehicle is in passive operation, heat may be transferred from the electrical storage system to the vehicle's surroundings.For example, the intensity of solar radiation, shading obstacles in the vehicle's vicinity, heat sources near the vehicle, etc., can influence the temperature development of the electrical storage device over time. Estimating a battery's state of charge solely based on the current ambient temperature and battery information, as described in the prior art explained above, can therefore lead to an inaccurate statement of the battery's performance characteristics. The invention allows for the consideration of positive and negative heat inputs into the electrical storage device over time, thus providing a more accurate prediction of the electrical storage device's temperature profile than is possible in the prior art. Accordingly, the performance characteristics of the electrical storage device can also be specified with greater accuracy.This can also be relevant, for example, for the control of semi-autonomous or autonomous vehicles. The method can thus provide an improved estimation of the performance characteristics of an electrical storage device.

[0011] Determining the site conditions, identifying the factors influencing temperature, and / or forecasting the temperature trend can be performed using at least one machine learning algorithm. A separate machine learning algorithm can be used for each of these steps. Alternatively, a single machine learning algorithm can be used for some or all of the described steps. The machine learning algorithm can, for example, be implemented as an artificial neural network. In other implementations, machine learning algorithms that do not necessarily have to be implemented as artificial neural networks can be used.

[0012] According to some embodiments, it is conceivable that the at least one further sensor may be designed to determine at least a location and / or an altitude above mean sea level, compass and map data, an obstacle in the vicinity of the vehicle, a battery charge level, an outside light value, a moisture level on the vehicle surface and / or an outside temperature.

[0013] With at least one of these pieces of information, a location assessment can be derived. For example, determining the location or altitude above sea level allows for the calculation of average solar radiation or the use of compass and / or map data. Knowing the time of day enables the use of a time-resolved average solar radiation for the location assessment. Knowing the mobile network signal strength or an ambient light level allows for an estimation of whether the vehicle is located inside or outside a building. It can also be estimated whether the building has open or solid walls, such as in a parking garage, carport, garage, or underground parking facility. Radar, lidar, and / or ultrasonic sensors can be used to determine obstacles near the vehicle and their distances, as these obstacles might cast shadows or emit heat themselves.The battery charge level, the ambient air temperature, and / or the humidity on the vehicle surface, which can be caused by precipitation, for example, can also be relevant for predicting future temperature trends. This allows the location situation to be derived with a high degree of accuracy.

[0014] According to some embodiments, it is conceivable that information about location-dependent times of sunrise and / or sunset and / or weather data, in particular air temperature forecasts, can be taken into account to determine the at least one influencing factor.

[0015] This information can be received from an external source, for example. Tables containing the relevant information can be transmitted from an external server to the vehicle. In this way, the vehicle's location can be determined with high accuracy.

[0016] According to some embodiments, it is conceivable that a past temperature profile can be taken into account when determining at least one influencing factor.

[0017] The past temperature history of the electrical storage device can thus be used to identify influencing factors for any predicted temperature trend. This allows for a more accurate determination of these influencing factors.

[0018] According to some embodiments, it is conceivable that the method, after the step of determining a forecast temperature profile, may further comprise at least the following step: After at least a partial period of the determined forecast profile lies in the past: Determine at least one actual temperature profile of the electrical storage device for at least one section of the partial period; compare the forecast profile with the determined actual temperature profile; and use at least one deviation between the forecast profile and the actual temperature profile to optimize the step of determining a forecast temperature profile.

[0019] This allows the temperature forecast to be checked and, if there is a deviation from the actual trend, the determination of the forecast trend can be adjusted.

[0020] According to some embodiments, it is conceivable that data about the optimized step: determining a predictive temperature trend, can be provided as an optimization signal to at least one other vehicle.

[0021] This allows a fleet of vehicles to benefit from the optimization of a single vehicle. Furthermore, optimization can be performed by multiple vehicles, which then share their optimization results. This can accelerate and improve the optimization of forecast trends.

[0022] According to some embodiments, it is conceivable that in the step: Determining at least one influencing factor, already known influencing factors for previous site situations with their associated previous starting temperatures can be taken into account.

[0023] For example, during the development phase of an electrical storage system, a heating curve and / or a cooling curve of the electrical storage system can be determined while it is not in operation. Furthermore, additional thermal masses of the vehicle can be taken into account. The curves can also be determined with different starting temperatures. This provides an initial basis for determining the factors influencing the temperature of the electrical storage system.

[0024] According to a second aspect, a computer program product is described, comprising instructions that, when the program is executed by a computer, cause it to perform the steps of the procedure according to the preceding description.

[0025] The advantages, effects, and further developments of the computer program product result from the advantages, effects, and further developments of the method described above. Therefore, reference is made to the preceding description in this regard. A computer program product can be understood, for example, as a data carrier on which a computer program element is stored, containing instructions executable by a computer. Alternatively or additionally, a computer program product can also be understood, for example, as a permanent or volatile data storage medium, such as flash memory or main memory, that contains the computer program element. However, this does not exclude other types of data storage media that contain the computer program element.

[0026] According to a third aspect, a vehicle is described comprising at least one electrical storage device, at least one temperature sensor for providing at least one temperature signal indicating the current temperature of the electrical storage device, at least one further sensor for providing at least one further sensor signal indicating data for deriving the vehicle's location, wherein the at least one further sensor is configured to determine at least a time and / or mobile phone reception quality, and at least one control unit connected to the further sensor and the temperature sensor via at least one signal connection, wherein the control unit is configured to perform the steps of the computer-implemented method according to the preceding description.

[0027] The advantages, effects, and further developments of the vehicle result from the advantages, effects, and further developments of the procedure described above. To avoid repetition, reference is therefore made to the preceding description in this regard.

[0028] According to a fourth aspect, a system is described comprising at least one computing unit and at least one vehicle with at least one electrical storage device, at least one temperature sensor for providing at least one temperature signal indicating the current temperature of the electrical storage device, at least one further sensor for providing at least one further sensor signal indicating data for deriving the vehicle's location, wherein the at least one further sensor is configured to determine at least a time and / or mobile network reception quality, wherein the computing unit is connected to the sensor and the temperature sensor via a signal connection, is located outside the vehicle and is configured to perform the steps of the computer-implemented method according to the preceding description.

[0029] By using a computing unit located outside the vehicle, a central processing unit can be used to execute the computer-implemented process. This relieves the burden on the vehicle's onboard computer. Furthermore, the use of the central processing unit allows for the optimization of an algorithm for predicting temperature trends at a central location, which can then be rolled out as an update to an entire vehicle fleet.

[0030] Further advantages, effects, and enhancements of the system arise from the advantages, effects, and enhancements of the vehicle and procedure described above. To avoid repetition, reference is made to the preceding description in this regard.

[0031] The invention is described below with reference to an exemplary embodiment and the accompanying drawing. The drawing shows: Fig. 1. A flowchart of the process; Fig. 2 a schematic representation of a vehicle; Fig. 3a-c schematic representations of site situations; and Fig. 4 a schematic representation of a system.

[0032] According to Fig. 1. The entire procedure would be designated by reference numeral 100.

[0033] Method 100 is designed to determine a predicted temperature profile of an electrical storage device 12 of a vehicle 10 in a passive operating state. The vehicle 10 is exemplified in Fig. 2 shown.

[0034] The vehicle 10 has a temperature sensor 14 on the electrical storage device 12. The temperature sensor 14 measures the temperature of the electrical storage device 12. Furthermore, the temperature sensor 14 provides a temperature signal that indicates the current temperature of the electrical storage device 12.

[0035] The vehicle 10 further comprises a control unit 22. The control unit 22 is connected to the temperature sensor 14 via a signal connection. Furthermore, the control unit 22 can be configured to execute the computer-implemented procedure 100. The signal connection can be wireless or wired.

[0036] For example, according to step 102, at least one temperature signal can be received by the control unit 22.

[0037] Furthermore, the vehicle 10 has at least one additional sensor 16-20. This additional sensor 16-20 can provide a further sensor signal that displays data for deriving information about the vehicle 10's location. The control unit 22 and the additional sensor 16-20 can also be connected to each other via a signal connection, which can be wireless or wired. In this way, the control unit 22 can also receive the additional sensor signal.

[0038] The additional sensor 16-20 can, for example, be a position sensor that can determine the location and / or altitude of the vehicle 10. The position sensor can, for example, be connected to a global satellite navigation network.

[0039] Alternatively or additionally, a further sensor 16-20 can be provided which, according to the invention, can determine a current time.

[0040] In some further embodiments, the additional transmitter 16-20 can be configured to provide compass and map data. This allows the vehicle's position and orientation to be determined.

[0041] According to the invention, the additional sensor 16-20 can determine the quality of mobile phone reception. For example, it can be determined whether the vehicle is located inside or outside a building.

[0042] Furthermore, in other embodiments, the additional sensor 16-20 can determine an outside light value. This allows the additional sensor 16-20 to determine whether it is light or dark outside the vehicle.

[0043] In some further embodiments, the additional sensor 16-20 can be configured to detect obstacles in the vicinity of the vehicle 10. In this way, for example, it is possible to detect whether the vehicle 10 is shaded by an obstacle or whether the vehicle 10 is in the slipstream of an obstacle.

[0044] Furthermore, the current battery charge level can be determined by the additional sensor 16-20 in some embodiments.

[0045] Alternatively or additionally, in some embodiments, the outside temperature of the air in the vicinity of the vehicle 10 can also be determined by the further sensor 16-20.

[0046] Furthermore, according to some embodiments, the additional sensor 16-20 can be used to detect moisture on the vehicle surface. For example, it can be determined whether cooling precipitation might be present on the vehicle surface.

[0047] In some embodiments, several additional sensors 16-20 may be provided, which can supply various pieces of information described above. The information described above can then be used alone or in combination to determine the location of the vehicle 10 according to step 104.

[0048] In the Fig. Figures 3a to 3c depict different location situations, although it should not be excluded that other location situations may exist.

[0049] According to Fig. 3a In the first location scenario, vehicle 10 is parked outdoors. Vehicle 10 is exposed to direct sunlight 24. Furthermore, heat can be transferred to vehicle 10 via a heated ground 26 or drawn away from vehicle 10 via a cooled ground 26. An obstacle 28 can, for example, act as a windbreak and / or reduce the sunlight 24 by casting a shadow.

[0050] According to Fig. In 3b, the vehicle 10 is positioned in a second location under a carport 30. The carport 30 can, for example, reduce solar radiation. However, additional positive or negative heat inputs into the vehicle 10 can occur due to a heated or cooled ground 26.

[0051] Fig. Figure 3c shows a vehicle positioned in garage 34 in a third location scenario. Furthermore, the location scenario is depicted at night, as symbolized by the moon 32. Therefore, there is no direct sunlight. The vehicle 10 is also sheltered from the wind in garage 34. Heating up or cooling down significantly of the floor 26 within garage 34 is unlikely.

[0052] In step 106, at least one influencing factor for the temperature of the electrical storage device 12 can be determined based on the location and the current temperature. The location and the current temperature are taken into account in this process.

[0053] An influencing factor for the temperature can be, for example, a quantity that causes a heat input to the electrical storage device 12, such as the presence or absence of solar radiation 24. Similarly, a blockage of a nearby heat input by an obstacle can also be an influencing factor for the temperature.

[0054] Furthermore, thermal radiation from a heated or cooled ground 26 can also be an influencing factor. Wind protection from neighboring vehicles or obstacles 28 in the vicinity can also be an influencing factor for the temperature of the electrical storage device 12.

[0055] In some embodiments, at least one piece of information about location-dependent sunrise and / or sunset times and / or weather data, in particular air temperature forecasts, can be taken into account to determine the at least one influencing factor. This allows, for example, the consideration of weather-dependent heat input to the electrical storage device when determining the influencing factors.

[0056] Furthermore, a recorded temperature profile of the electrical storage device 12 from the past can also be taken into account when determining the influencing factors. Thus, from the recorded temperature profile and any information about influencing factors recorded at that past time or time period, it is possible to deduce which influencing factors can be considered for the temperature forecast.

[0057] Furthermore, investigations may have already been carried out during the development of the vehicle 10 to determine how the temperature of the electrical storage device 12 of the vehicle 10 develops in passive operation under various conditions. For example, different starting temperatures can be used and heating and / or cooling curves of the electrical storage device 12, including the thermal masses of the vehicle 10, can be taken into account.

[0058] In a further step 108, a predicted temperature profile of the electrical storage device 12 can be determined based on the identified influencing factors. The predicted profile can start from the current temperature.

[0059] Using the forecast curve, a performance characteristic of the electrical storage device 12 can be specified with increased accuracy at the current time.

[0060] Since part of the predicted temperature history lies in the past, an actual temperature history for the electrical storage device 12 can be determined in a further optional step 110 after step 108 for at least part of the past time period. To obtain an actual temperature history for the electrical storage device 12, the temperature signal from the temperature sensor can, for example, be read and stored at regular intervals.

[0061] In a further optional step 112, the actual temperature profile can be compared with the corresponding partial period of the forecast. This comparison allows for the identification of deviations between the forecast and the actual temperature profile.

[0062] The deviations can be used in a further optional step 114 to optimize step 108. For example, an algorithm on which step 108 is based can be modified and subjected to an optimization procedure.

[0063] The algorithm could, for example, be designed as an artificial neural network. However, it is also conceivable that the algorithm is not designed as an artificial neural network but is nevertheless capable of learning.

[0064] The information about the optimization of step 108 can be provided to other vehicles 38 as an optimization signal in a further optional step 116. This can be done, for example, via a direct connection 42 between the vehicles or via an intermediate station, such as a stationary server 36, as exemplified in Fig. 4 is shown.

[0065] The stationary server 36 can be configured as a computing unit 36 ​​to perform the procedure 100 described above. The computing unit 36 ​​can receive the necessary signals from the vehicle 10 via a signal connection 40, preferably wireless, in order to perform a prediction of the temperature profile of the electrical storage device 12 of the vehicle 10.

[0066] The example described above does not in any way limit the invention. Rather, the invention can be modified in numerous ways. All features of the invention described above can be essential to the invention, either alone or in combination. Reference symbol list 10 vehicles 12 electrical storage units 14 Temperature sensor 16 Sensor 18 Sensor 20 Sensor 22 Control unit 24 Sunlight 26 Floor 28th obstacle 30 Carport 32 Moon 34 Garage 36 computing units 38 vehicles 40 Signal connection 42 Signal connection

Claims

[1] Computer-implemented method (100) for determining a predictive temperature profile of an electrical storage device (12) of a vehicle (10) in a passive operating state, comprising at least one temperature sensor (14) for providing at least one temperature signal indicating a current temperature of the electrical storage device (12), and at least one further sensor (16-20) for providing at least one further sensor signal indicating data for deriving a location situation of the vehicle (10), wherein the at least one further sensor (16-20) is configured to determine at least a time and / or a mobile network reception quality, wherein the method (100) comprises at least the following steps: a. Receiving (102) the at least one temperature signal and the at least one other sensor signal; b. Determining (104) the location of the vehicle (10) from the received additional sensor signal; c. Determine (106) at least one influencing factor for the temperature of the electrical storage (12) taking into account the site conditions and the current temperature; and d. Determining (108) a predictive trend of the temperature of the electrical storage (12) based on the determined influencing factors and starting from the current temperature. [2] Computer-implemented method (100) according to claim 1, characterized by , that the at least one further sensor (16-20) is further designed at least to determine a location and / or an altitude above mean sea level, compass and map data, an obstacle in the vicinity of the vehicle (10), a battery charge level and / or an outside temperature, an outside light value and / or a moisture level on the vehicle surface. [3] Computer-implemented method (100) according to claim 1 or 2, characterized by, that in order to determine (106) the at least one influencing factor, information on location-dependent times of sunrise and / or sunset and / or weather data, in particular air temperature forecasts, shall be taken into account. [4] Computer-implemented method (100) according to any one of the preceding claims, characterized by , that a past temperature trend is taken into account when determining (106) the at least one influencing factor. [5] Computer-implemented method (100) according to any one of the preceding claims, characterized by , that the procedure (100) after the step: Determining (108) a forecast trend of the temperature, further comprises at least the following step: a. Since at least one part of the determined forecast period lies in the past: Determine (110) at least one actual temperature profile of the electrical storage (12) for at least one section of the part of the period; b. Comparing (112) the forecast trend with the determined actual temperature trend; and c. Use (114) at least one deviation between the forecast trend and the actual temperature trend to optimize the step: Determine (108) a forecast trend of the temperature. [6] Computer-implemented method (100) according to claim 5, characterized by , that data on the optimized step: Determining (108) a forecast trend of the temperature, as an optimization signal are provided to at least one other vehicle (116). [7] Computer-implemented method (100) according to any one of the preceding claims, characterized by , that in step: Determine (106) at least one influencing factor, already known influencing factors for previous site situations with their associated previous starting temperatures are taken into account. [8] Computer program product comprising instructions which, when the program is executed by a computer, cause it to perform the steps of the method (100) according to any one of claims 1 to 7. [9] Vehicle (10) comprising at least one electrical storage device (12), at least one temperature sensor (14) for providing at least one temperature signal indicating the current temperature of the electrical storage device (12), at least one further sensor (16-20) for providing at least one further sensor signal indicating data for deriving the location of the vehicle (10), wherein the at least one further sensor (16-20) is configured to determine at least a time and / or a mobile communication reception quality, and at least one control unit (22) which is connected to the further sensor (16-20) and the temperature sensor (14) via at least one signal connection (40, 42), wherein the control unit (22) is configured to perform the steps of the computer-implemented method (100) according to any one of claims 1 to 7. [10] System comprising at least one computing unit (36) and at least one vehicle (10) with at least one electrical storage device (12), at least one temperature sensor (14) for providing at least one temperature signal indicating the current temperature of the electrical storage device (12), at least one further sensor (16-20) for providing at least one further sensor signal indicating data for deriving the location of the vehicle (10), wherein the at least one further sensor (16-20) is configured at least for determining a time and / or a mobile communication reception quality, wherein the computing unit (36) is connected to the sensor (16-20) and the temperature sensor (14) via a signal connection (40, 42), is arranged outside the vehicle (10) and is configured for carrying out the steps of the computer-implemented method (100) according to one of claims 1 to 7.

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