Computer-implemented method for determining a forecast curve of a temperature of an electrical storage device, vehicle and system

Abstract

The invention relates to a computer-implemented method (100) for determining a forecast curve of a temperature of an electrical storage device (12) of a vehicle (10) in a passive operating state, which comprises 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 method (100) comprises at least the following steps: receiving (102) the at least one temperature signal and the at least one further sensor signal; determining (104) a location situation of the vehicle (10) from the received further sensor signal;Determining (106) at least one influencing variable for the temperature of the electrical storage device (12) taking into account the location situation and the current temperature; and determining (108) a forecast curve for the temperature of the electrical storage device (12) based on the determined influencing variables and starting from the current temperature. The computer-implemented method (100) provides an improved estimate of the performance characteristics of the electrical storage device (12).

Description

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

[0002] The performance characteristics of electrical storage devices can be represented, for example, in the form of the state of charge, ranging from 0% to 100%. They depend heavily on the temperature of the electrical storage device. If temperatures are too high or too low compared to the optimal operating temperature range for the electrical storage device, the performance characteristics deteriorate. For example, if the electrical storage device is installed in an electrically powered vehicle and the vehicle is parked at low temperatures in the range of -10°C, the displayed performance characteristics may have changed at a later time compared to the time of storage.

[0003] WO2023157278A1 discloses a battery state estimation device comprising a vehicle data acquisition unit, a temperature data acquisition unit, and an estimation unit. The vehicle data acquisition unit acquires vehicle stop position information and battery information. The vehicle stop position information indicates a vehicle stop position of a vehicle equipped with a battery. The battery information indicates the state of the battery at the position where the vehicle has stopped. The temperature data acquisition unit acquires temperature data, which is data related to the temperature at the vehicle stop position, using the vehicle stop 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] 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.

[0005] 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.

[0006] According to a first aspect, a computer-implemented method for determining a forecast curve for a temperature of an electrical storage device of a vehicle in a passive operating state is described, which has at least one temperature sensor for providing at least one temperature signal indicating a current temperature of the electrical storage device, and at least one further sensor for providing at least one further sensor signal indicating data for deriving a location situation of the vehicle, wherein the method comprises at least the following steps: receiving the at least one temperature signal and the at least one further sensor signal; determining a location situation of the vehicle from the received further sensor signal; determining at least one influencing variable for the temperature of the electrical storage device taking into account the location situation and the current temperature;and determining a forecast curve for the temperature of the electrical storage device based on the determined influencing factors and starting from the current temperature.;

[0007] The computer-implemented method provides a forecast for the temperature profile of an electrical storage unit in a vehicle during passive operation. The vehicle's location is taken into account when creating the forecast. The forecast temperature profile of the electrical storage unit can then be used to draw conclusions about the future performance characteristics of the electrical storage unit, such as the state of charge. A passive operating state is understood to be a non-driving state of the vehicle. The vehicle can be in a passive operating state when it is stopped or parked. The data from the additional sensor signal can be used to draw conclusions about the vehicle's location. Depending on the location in which the vehicle is in passive operating mode, heat can be input or output from the electrical storage unit to the vehicle's surroundings.For example, the intensity of solar radiation, shading obstacles in the vehicle's surroundings, heat sources near the vehicle, etc. can influence the development of the temperature of the electrical storage device over time. Estimating a battery's condition solely based on the current outside temperature and battery information, as described in the prior art explained above, can therefore lead to an inaccurate indication of the battery's performance characteristics. The invention allows the positive and negative heat inputs into the electrical storage device over time to be taken into account, thus providing a more accurate forecast of the temperature development of the electrical storage device than in the prior art. Accordingly, the performance characteristics of the electrical storage device can also be specified with greater accuracy.This could also be relevant, for example, for the control of semi-autonomous or autonomous vehicles. The method can thus provide an improved estimate of the performance characteristics of an electrical storage device.

[0008] The determination of the location situation and / or the determination of the influencing factors for the temperature and / or the determination of the forecast temperature profile can be carried out using at least one adaptive algorithm. A separate adaptive algorithm can be used for each of the aforementioned determination steps. Alternatively, a common adaptive algorithm can be used for some or all of the described determination steps. The adaptive algorithm can be implemented, for example, as an artificial neural network. In other embodiments, adaptive algorithms can be used that do not necessarily have to be implemented as an artificial neural network.

[0009] According to some embodiments, it is conceivable that the at least one further sensor can be designed at least to determine a location and / or an altitude above sea level, a time of day, compass and map data, a mobile radio reception quality, an outside light value, an obstacle in an environment of the vehicle, a battery charge state, an outside temperature and / or a humidity on the vehicle surface.

[0010] A location situation can be derived using at least one of these pieces of information. For example, average solar radiation can be calculated by determining the location or an altitude above sea level, or using compass and / or map data. With knowledge of the time, a time-resolved average solar radiation can be used for the location situation. With knowledge of the quality of mobile phone reception or an outside light value, it can be estimated whether the vehicle can be parked inside or outside a building. It can also be estimated whether the building has open walls or solid walls, for example in a parking garage or carport or in a garage or underground parking garage. Radar, lidar and / or ultrasonic sensors can be used to determine obstacles in the vicinity of the vehicle and the distance to the obstacles that could potentially cast shadows or radiate heat.The battery charge level, outside air temperature, and / or humidity on the vehicle surface, which can be generated by precipitation, for example, can also be relevant for future temperature trends. This allows the location situation to be derived with high accuracy.

[0011] 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 variable.

[0012] This information can be received from an external source, for example. For example, tables containing the relevant information can be transmitted from an external server to the vehicle. This allows the location situation to be determined with high accuracy.

[0013] According to some embodiments, it is conceivable that a past temperature profile can be taken into account when determining the at least one influencing variable.

[0014] The past temperature history of the electrical storage system can thus be used to identify influencing factors for each forecast temperature trend. The determination of influencing factors can thus be carried out with increased accuracy.

[0015] According to some embodiments, it is conceivable that the method, after the step of determining a forecast profile of the temperature, can further comprise at least the following step: After at least a partial period of the determined forecast profile lies in the past: determining at least one actual temperature profile of the electrical storage device for at least a portion of the partial period; comparing the forecast profile with the determined actual temperature profile; and using at least one deviation between the forecast profile and the actual temperature profile to optimize the step of determining a forecast profile of the temperature.

[0016] This allows the temperature forecast to be checked and, if there is a deviation from the actual temperature, the forecast can be adjusted.

[0017] According to some embodiments, it is conceivable that data about the optimized step: determining a forecast course of the temperature, can be provided as an optimization signal to at least one other vehicle.

[0018] This allows a fleet of vehicles to benefit from the optimization of one vehicle. Furthermore, optimization can be performed by multiple vehicles, which then share their optimization results with each other. This can accelerate and improve the optimization of forecast processes.

[0019] According to some embodiments, it is conceivable that in the step of determining at least one influencing variable, already known influencing variables for previous location situations with their associated previous starting temperatures can be taken into account.

[0020] For example, during a development phase of the electric storage system, a heating and / or cooling curve of the electric storage system can be determined during inactive operation. Furthermore, additional thermal masses of the vehicle can be taken into account. The curves can also be determined with different starting temperatures. This can provide an initial basis for determining the factors influencing the temperature of the electric storage system.

[0021] According to a second aspect, a computer program product is described, comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of the method according to the preceding description.

[0022] Advantages and effects, as well as further developments of the computer program product, arise from the advantages and effects, as well as further developments of the method described above. Reference is therefore made to the preceding description in this regard. A computer program product can be understood, for example, as a data storage medium on which a computer program element is stored that contains 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 device, such as flash memory or RAM, that contains the computer program element. However, this does not exclude other types of data storage devices that contain the computer program element.

[0023] 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 a current temperature of the electrical storage device, at least one further sensor for providing at least one further sensor signal indicating data for deriving a location situation of the vehicle, 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 designed to carry out the steps of the computer-implemented method according to the preceding description.

[0024] Advantages and effects, as well as further developments of the vehicle, arise from the advantages and effects, as well as further developments of the method described above. To avoid repetition, reference is made to the previous description in this regard.

[0025] 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 that indicates a current temperature of the electrical storage device, at least one further sensor for providing at least one further sensor signal that indicates data for deriving a location situation of the vehicle, wherein the computing unit is connected to the sensor and the temperature sensor via a signal connection, is arranged outside the vehicle and is designed to carry out the steps of the computer-implemented method according to the preceding description.

[0026] By using a processing unit located outside the vehicle, for example, a central processing unit can be used to carry out the computer-implemented process. This can reduce the load on a vehicle's on-board computer. Furthermore, by using the central processing unit, an algorithm for determining a temperature forecast can be optimized centrally and, after optimization, rolled out as an update to a vehicle fleet.

[0027] Further advantages and effects, as well as further developments of the system, arise from the advantages and effects, as well as further developments of the vehicle and method described above. To avoid repetition, reference is made to the previous description in this regard.

[0028] The invention is described below using an exemplary embodiment with reference to the accompanying drawings. They show: Fig. 1 a flow chart 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.

[0029] According to Fig. 1, the process as a whole would be designated by the reference numeral 100.

[0030] The method 100 is designed to determine a forecast curve of a temperature of an electrical storage device 12 of a vehicle 10 in a passive operating state. The vehicle 10 is shown, for example, in Fig. 2 shown.

[0031] The vehicle 10 has a temperature sensor 14 on the electrical storage unit 12. The temperature sensor 14 measures the temperature of the electrical storage unit 12. Furthermore, the temperature sensor 14 provides a temperature signal indicating the current temperature of the electrical storage unit 12.

[0032] The vehicle 10 further includes 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 carry out the computer-implemented method 100. The signal connection can be wireless or wired.

[0033] For example, according to step 102, the at least one temperature signal can be received by the control unit 22.

[0034] Furthermore, the vehicle 10 has at least one additional sensor 16-20. The additional sensor 16-20 can provide an additional sensor signal that indicates data for deriving from the location situation of the vehicle 10. 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.

[0035] The additional sensor 16-20 can, for example, be a position sensor with which the location and / or an altitude above sea level of the vehicle 10 can be determined. The position sensor can, for example, be connected to a global satellite navigation network.

[0036] Alternatively or additionally, a further sensor 16-20 can be provided, which can, for example, determine the current time.

[0037] In some further embodiments, the additional transmitter 16-20 may be configured to provide compass and map data. This allows the position and orientation of the vehicle to be determined.

[0038] In some other embodiments, the additional sensor 16-20 can determine the quality of mobile radio reception. For example, it can be determined whether the vehicle can be located inside or outside a building.

[0039] Furthermore, in further 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.

[0040] In some further embodiments, the further sensor 16-20 can be configured to detect obstacles in the surroundings of the vehicle 10. In this way, for example, a shadow of the vehicle 10 by an obstacle or a slipstream of an obstacle in which the vehicle 10 may be located can be detected.

[0041] Furthermore, a current battery charge level can be determined by the additional sensor 16-20 in some embodiments.

[0042] Alternatively or additionally, in some embodiments, an outside temperature of the air in the surroundings of the vehicle 10 can also be determined by the further sensor 16-20.

[0043] Furthermore, in 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 may be present on the vehicle surface.

[0044] In some embodiments, several additional sensors 16-20 may be provided, which can provide various of the information explained above. The information explained above can be used alone or in combination with one another to determine a location situation of the vehicle 10 according to step 104.

[0045] In the Fig. Figures 3a to 3c show various location situations, although it should not be excluded that further location situations may exist.

[0046] According to Fig. 3a, the vehicle 10 is parked outdoors in a first location. The vehicle 10 is exposed to direct sunlight 24. Furthermore, heat can be transferred to the vehicle 10 via a heated floor 26 or removed from the vehicle 10 via a cooled floor 26. An obstacle 28 can, for example, act as a windbreak and / or reduce the solar radiation 24 by casting a shadow.

[0047] According to Fig. 3b, the vehicle 10 is arranged 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 through a heated or cooled floor 26.

[0048] Fig. 3c shows a vehicle arranged in a garage 34 in a third location. Furthermore, the location is depicted at a time when it is night, as symbolized by the moon 32. Therefore, solar radiation is not present. Likewise, the vehicle 10 is protected from the wind in the garage 34. Heating or significant cooling of the floor 26 within the garage 34 is unlikely.

[0049] Using the location and the current temperature, at least one influencing factor for the temperature of the electrical storage device 12 can be determined in step 106. The location and the current temperature are taken into account in this process.

[0050] An influencing factor for the temperature can, for example, be a factor that causes heat input to the electrical storage device 12, such as the presence or absence of solar radiation 24. Also, for example, a blockage of a nearby heat input by an obstacle can be an influencing factor for the temperature.

[0051] Furthermore, thermal radiation from a heated or cooled floor 26 can also be an influencing factor. Wind protection from neighboring vehicles or obstacles 28 in the surrounding area can also be an influencing factor for the temperature of the electrical storage device 12.

[0052] 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, a weather-dependent heat input to the electrical storage device to be taken into account when determining the influencing factors.

[0053] Furthermore, a historically recorded temperature profile of the electrical storage device 12 can also be taken into account when determining the influencing factors. Thus, from the recorded temperature profile and, if applicable, information about influencing factors recorded at this past time or period, it is possible to determine which influencing factors can be considered for the forecast temperature profile.

[0054] Furthermore, during the development of the vehicle 10, investigations may have already been conducted into how the temperature of the electrical storage unit 12 of the vehicle 10 develops during passive operation under various conditions. For example, different starting temperatures may be used, and heating and / or cooling curves of the electrical storage unit 12, including the thermal masses of the vehicle 10, may be taken into account.

[0055] In a further step 108, a forecast curve for the temperature of the electrical storage device 12 can be determined based on the determined influencing variables. The forecast curve can start from the current temperature.

[0056] By means of the forecast curve, a performance characteristic of the electrical storage device 12 at the current time can be specified with increased accuracy.

[0057] Since part of the predicted temperature profile lies in the past, an actual temperature profile for the electrical storage device 12 can be determined for at least part of the past time period in a further optional step 110 following step 108. To obtain an actual temperature profile for the electrical storage device 12, the temperature signal from the temperature sensor can be read and stored at regular intervals, for example.

[0058] In a further optional step 112, the actual temperature curve can be compared with the partial period of the forecast curve. From this comparison, deviations between the forecast curve and the actual temperature curve can be determined.

[0059] Using the deviations, an optimization of step 108 can be performed in a further optional step 114. For example, an algorithm on which step 108 is based can be modified and subjected to an optimization process.

[0060] The algorithm can, 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 still capable of learning.

[0061] 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, for example in the form of a stationary server 36, as exemplified in Fig. 4 is shown.

[0062] The stationary server 36 can be configured as a computing unit 36 ​​to carry out the method 100 explained above. Via a preferably wireless signal connection 40, the computing unit 36 ​​can receive the necessary signals from the vehicle 10 in order to make a prediction about the temperature profile of the electrical storage unit 12 of the vehicle 10.

[0063] The example described above does not limit the invention in any way. Rather, the invention can be modified in many ways. All of the features of the invention described above can be essential to the invention alone or in combination with one another. List of reference symbols 10 vehicles 12 electrical storage 14 Temperature sensor 16 sensors 18 Sensor 20 sensors 22 Control unit 24 solar radiation 26 Floor 28 Obstacle 30 Carport 32 Moon 34 Garage 36 computing unit 38 vehicles 40 Signal connection 42 Signal connection QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] WO 2023157278A1

[0003]

Claims

[1] Computer-implemented method (100) for determining a predictive trend of the temperature 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 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 designed to determine at least a location and / or an altitude above mean sea level, a time, compass and map data, a mobile phone reception quality, an outside light value, an obstacle in the vicinity of the vehicle (10), a battery charge level, an outside temperature and / or a humidity 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 a 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 a location situation of the vehicle (10), 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 a 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 a location situation of the vehicle (10), 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 to perform the steps of the computer-implemented method (100) according to one of claims 1 to 7.

Images