A method and system for predicting temperature and thermal management energy consumption based on navigation charging

Abstract

The application discloses a kind of prediction method and system based on navigation charging temperature and thermal management energy consumption, belong to new energy automobile field, the method includes: by SOC module and residual time module, the BMS of first vehicle is calculated in power-on update state, set navigation state and start navigation state, whether the first vehicle is currently selected stake is judged;If select stake, first cycle information is calculated and updated, obtain second cycle information;If in start navigation state, obtain third cycle information;Third cycle information is analyzed using intelligent temperature control module, generate first prediction information.Solve the technical problems that cannot accurately predict temperature and thermal management energy consumption in real time after obtaining navigation information in the prior art.Accurately predict temperature and thermal management energy consumption based on navigation information, thereby improve the accuracy of navigation, improve the technical effects of vehicle operation stability and service life.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy vehicles, and in particular to a temperature and thermal management energy consumption prediction method and system based on navigation charging. BACKGROUND

[0002] With the continuous progress of economy and technology, automobiles will also develop towards high electrification and intelligence. New energy vehicles use new energy to power the vehicle, greatly reducing the impact of vehicle emissions on the environment. Therefore, researching and optimizing new energy vehicle technology is of great significance for optimizing resource allocation and reducing the burden of traditional energy in China.

[0003] Currently, the power management of new energy vehicles is mainly through the battery management system (Battery management system, BMS) of electric vehicles, which can realize real-time monitoring, automatic balancing, intelligent charging and discharging, etc. of the battery. While effectively ensuring the safety of the battery, it can detect the remaining power of the battery, effectively manage the battery, and ensure the safety and reliability of the battery or battery pack to output power in the best state.

[0004] However, since the existing BMS system cannot accurately manage the temperature and thermal management energy consumption based on actual navigation information after obtaining user navigation information, it further leads to unsafe vehicle charging, and there is no technology to accurately predict the temperature and thermal management energy consumption in real time after obtaining navigation information, and to provide intelligent and accurate navigation planning. SUMMARY

[0005] The purpose of the present application is to provide a temperature and thermal management energy consumption prediction method and system based on navigation charging, to solve the technical problem that the prior art cannot accurately predict the temperature and thermal management energy consumption in real time after obtaining navigation information, and provide intelligent and accurate navigation planning.

[0006] To solve the above technical problems, the present application provides a temperature and thermal management energy consumption prediction method based on navigation charging. The method is applied to a temperature and thermal management energy consumption prediction system based on navigation charging. The system is in communication connection with a BMS, and the BMS includes a state of charge (State Of Charge, SOC) module, a remaining time module, and an intelligent temperature control module. The method comprises:

[0007] According to the SOC module, the BMS of the first vehicle in the power-up update state is calculated, and the first cycle information is sent.

[0008] acquire a first state of the first vehicle in real time, and determine whether the first state conforms to a first preset navigation state, wherein the first preset navigation state is a set navigation state in a guide navigation state;

[0009] If the first state conforms to the first preset navigation state, acquire a first route selection planning, and determine whether the first vehicle is currently performing selection of the column according to the first route selection planning;

[0010] If the first vehicle is currently performing selection of the column, update the first cycle information by using the SOC module and the remaining time module to obtain second cycle information;

[0011] Acquire a second state of the first vehicle by updating the first state in real time, and determine whether the second state conforms to a second preset navigation state, wherein the second preset navigation state is a start navigation state in the guide navigation state;

[0012] If the second state conforms to the second preset navigation state, update the second cycle information by using the SOC module and the remaining time module to obtain third cycle information;

[0013] Analyze the third cycle information by using the intelligent temperature control module to generate first prediction information.

[0014] Preferably, the method as described above, if the first state conforms to the first preset navigation state, acquiring a first route selection planning, previously comprises:

[0015] If the first state conforms to the first preset navigation state, update the first cycle information by using the SOC module to obtain fourth cycle information;

[0016] The fourth cycle information refers to the BMS of the first vehicle in the set navigation state, and the fourth cycle information is calculated by the SOC module.

[0017] Specifically, the method as described above, updating the first cycle information by using the SOC module and the remaining time module to obtain second cycle information, comprises:

[0018] Calculate the BMS of the first vehicle by using the SOC module to obtain first information;

[0019] Calculate the BMS of the first vehicle by using the remaining time module to obtain second information;

[0020] According to the first information and the second information, the second cycle information is composed, wherein the second cycle information refers to the BMS of the first vehicle in the selection of the column calculation state.

[0021] Preferably, the method as described above, the second periodic information is composed according to the first information and the second information, and then includes:

[0022] The second periodic information is analyzed by the intelligent temperature control module to obtain a first analysis result.

[0023] According to the first analysis result, the second prediction information is generated, wherein the second prediction information includes the prediction of the temperature and thermal management energy consumption of the first vehicle in the selected calculation state.

[0024] Specifically, the method as described above, the second state is determined whether to meet the second preset navigation state, and further includes:

[0025] If the second state does not meet the second preset navigation state, a first judgment instruction is obtained.

[0026] According to the first judgment instruction, the selected calculation state of the first vehicle is determined.

[0027] If the first vehicle is not successful in selecting the calculation, a first reminder instruction is obtained.

[0028] Specifically, the method as described above, the second periodic information is calculated and updated by the SOC module and the remaining time module to obtain third periodic information, including:

[0029] The BMS of the first vehicle is calculated by the SOC module to obtain third information.

[0030] The BMS of the first vehicle is calculated by the remaining time module to obtain fourth information.

[0031] According to the third information and the fourth information, the third periodic information is composed, wherein the third periodic information refers to the BMS of the first vehicle in the starting navigation state.

[0032] Further, the method as described above, the third periodic information is composed according to the third information and the fourth information, and then includes:

[0033] The third periodic information is analyzed by the intelligent temperature control module to obtain a second analysis result.

[0034] According to the second analysis result, the first prediction information is generated, wherein the first prediction information includes the prediction of the temperature and thermal management energy consumption of the first vehicle in the starting navigation state.

[0035] Another embodiment of the present application also provides a navigation charging temperature and thermal management energy consumption prediction system, the system comprising:

[0036] A first sending unit is configured to calculate first cycle information of the BMS of the first vehicle in the power-on update state according to the SOC module;

[0037] A first judging unit is configured to collect a first state of the first vehicle in real time and determine whether the first state conforms to a first preset navigation state, wherein the first preset navigation state is a set navigation state in a guide navigation state;

[0038] A second judging unit is configured to collect first route selection planning if the first state conforms to the first preset navigation state and determine whether the first vehicle is currently performing selection according to the first route selection planning;

[0039] A first obtaining unit is configured to update the first cycle information by using the SOC module and the remaining time module to obtain second cycle information if the first vehicle is currently performing selection;

[0040] A third judging unit is configured to collect a second state by updating the first state in real time and determine whether the second state conforms to a second preset navigation state, wherein the second preset navigation state is a start navigation state in the guide navigation state;

[0041] A second obtaining unit is configured to update the second cycle information by using the SOC module and the remaining time module to obtain third cycle information if the second state conforms to the second preset navigation state;

[0042] A first generating unit is configured to analyze the third cycle information by using an intelligent temperature control module to generate first prediction information.

[0043] Further, the system further comprises:

[0044] A third obtaining unit is configured to update the first cycle information by using the SOC module to obtain fourth cycle information if the first state conforms to the first preset navigation state;

[0045] A first setting unit is configured to set the fourth cycle information, wherein the fourth cycle information refers to the BMS of the first vehicle in the set navigation state, and the fourth cycle information is calculated by the SOC module.

[0046] Further, the system further comprises:

[0047] A fourth obtaining unit is configured to obtain first information by calculating BMS of the first vehicle by using the SOC module;

[0048] A fifth obtaining unit is configured to obtain second information by calculating BMS of the first vehicle by using the remaining time module;

[0049] A first composing unit is configured to compose the second period information according to the first information and the second information, wherein the second period information refers to BMS of the first vehicle in the selected calculation state.

[0050] Further, the system further comprises:

[0051] A sixth obtaining unit is configured to obtain a first analysis result by analyzing the second period information by using the intelligent temperature control module;

[0052] A second generating unit is configured to generate second prediction information according to the first analysis result, wherein the second prediction information comprises prediction of temperature and thermal management energy consumption of the first vehicle in the selected calculation state.

[0053] Further, the system further comprises:

[0054] A seventh obtaining unit is configured to obtain a first judgment instruction if the second state does not conform to the second preset navigation state;

[0055] A fourth judging unit is configured to judge the selected state of the first vehicle according to the first judgment instruction;

[0056] An eighth obtaining unit is configured to obtain a first reminding instruction if the first vehicle is not successfully selected.

[0057] Further, the system further comprises:

[0058] A ninth obtaining unit is configured to obtain third information by calculating BMS of the first vehicle by using the SOC module;

[0059] A tenth obtaining unit is configured to obtain fourth information by calculating BMS of the first vehicle by using the remaining time module;

[0060] The second constituent unit is configured to constitute the third periodic information according to the third information and the fourth information, wherein the third periodic information refers to the BMS of the first vehicle in a starting navigation state.

[0061] Further, the system further comprises:

[0062] The eleventh obtaining unit is configured to analyze the third periodic information by using the intelligent temperature control module to obtain a second analysis result.

[0063] The third generating unit is configured to generate the first prediction information according to the second analysis result, wherein the first prediction information comprises a prediction of the temperature and thermal management energy consumption of the first vehicle in a starting navigation state.

[0064] Still another embodiment of the present application further provides an electronic device comprising a processor and a memory;

[0065] The memory is configured to store:

[0066] The processor is configured to execute the method as described above by calling.

[0067] Still another embodiment of the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the method as described above.

[0068] Compared with the prior art, the method and system for predicting temperature and thermal management energy consumption based on navigation charging provided by the embodiments of the present application have at least the following beneficial effects:

[0069] The SOC module and the remaining time module are used to calculate the BMS of the first vehicle in a power-on updating state, a setting navigation state and a starting navigation state, and to determine whether the first vehicle is currently performing a pole selection; if the pole selection is performed, the first periodic information is calculated and updated to obtain second periodic information; if the first vehicle is in the starting navigation state, third periodic information is obtained; the intelligent temperature control module is used to analyze the third periodic information to generate first prediction information. The method realizes accurate prediction of temperature and thermal management energy consumption based on navigation information, thereby improving the accuracy of navigation and improving the technical effects of vehicle operation stability and service life. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 FIG. 1 is a flowchart of one of the methods for predicting temperature and thermal management energy consumption based on navigation charging according to the present application;

[0071] Figure 2Fig. 2 is a flowchart illustrating a method for predicting temperature and thermal management energy consumption based on navigation charging according to an embodiment of the present application;

[0072] Figure 3 Fig. 3 is a flowchart illustrating a method for predicting temperature and thermal management energy consumption based on navigation charging according to an embodiment of the present application;

[0073] Figure 4 Fig. 4 is a flowchart illustrating a method for predicting temperature and thermal management energy consumption based on navigation charging according to an embodiment of the present application;

[0074] Figure 5 Fig. 5 is a flowchart illustrating a method for predicting temperature and thermal management energy consumption based on navigation charging according to an embodiment of the present application;

[0075] Figure 6 Fig. 6 is a flowchart illustrating a method for predicting temperature and thermal management energy consumption based on navigation charging according to an embodiment of the present application;

[0076] Figure 7 Fig. 7 is a structural diagram of a system for predicting temperature and thermal management energy consumption based on navigation charging according to an embodiment of the present application;

[0077] Figure 8 Fig. 8 is a structural diagram of an exemplary electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0078] To make the technical problems to be solved, technical solutions and advantages of the present application clearer, specific embodiments will be described in detail below with reference to the accompanying drawings. In the following description, specific details such as specific configurations and components are provided only to help a comprehensive understanding of embodiments of the present application. Therefore, it should be apparent to those skilled in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, descriptions of known functions and configurations are omitted for clarity and conciseness.

[0079] It should be understood that the term "one embodiment" or "an embodiment" as used throughout this specification means that a particular feature, structure or characteristic described in connection with an embodiment is included in at least one embodiment of the present application. Therefore, the appearance of "in one embodiment" or "in an embodiment" at various places throughout the specification is not necessarily referring to the same embodiment. In addition, these particular features, structures or characteristics can be combined in any suitable manner in one or more embodiments.

[0080] In various embodiments of the present application, it should be understood that the size of the serial number of the following processes does not mean the order of execution, and the execution order of the processes should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0081] It should be understood that the term "and / or" in this document merely describes an associated relationship between associated objects, which means that there can be three relationships, for example, A and / or B can represent three cases: A exists alone, A and B exist together, and B exists alone. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after it.

[0082] In the embodiments provided in the present application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that the determination of B according to A does not mean that B is determined only according to A, but B can also be determined according to A and / or other information.

[0083] The present application provides a prediction method and system for temperature and thermal management energy consumption based on navigation, which solves the technical problem that the existing technology cannot accurately predict temperature and thermal management energy consumption in real time after obtaining navigation information, and provides intelligent and accurate navigation planning. The technical effect of accurately predicting temperature and thermal management energy consumption based on navigation information, thereby improving the accuracy of navigation, improving the stability and service life of the automobile.

[0084] In the technical solution of the present application, the acquisition, storage, use, processing and the like of data all comply with the relevant provisions of national laws and regulations.

[0085] Hereinafter, the technical solutions in the present application will be described clearly and completely with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present application. In addition, it should be noted that, for convenience of description, only parts related to the present application are shown in the drawings, not all.

[0086] This application provides a method for predicting temperature and thermal management energy consumption based on navigation charging. The method is implemented through a prediction system for temperature and thermal management energy consumption based on navigation charging. The system is communicatively connected to a BMS (Battery Management System), and the BMS includes a SOC (State of Charge) module, a remaining time module, and an intelligent temperature control module. The method includes: calculating the BMS status of a first vehicle in a power-on update state based on the SOC module, and sending first cycle information; real-time acquisition of the first state of the first vehicle, and determining whether the first state conforms to a first preset navigation state, wherein the first preset navigation state refers to the navigation state settings; if the first state conforms to the first preset navigation state, acquiring a first route selection and planning data, and... Based on the first route selection plan, it is determined whether the first vehicle is currently selecting a station. If the first vehicle is currently selecting a station, the first cycle information is calculated and updated using the SOC module and the remaining time module to obtain the second cycle information. The first state is collected and updated in real time to obtain the second state, and it is determined whether the second state conforms to the second preset navigation state, wherein the second preset navigation state refers to the start navigation state in the navigation state. If the second state conforms to the second preset navigation state, the second cycle information is calculated and updated using the SOC module and the remaining time module to obtain the third cycle information. The third cycle information is analyzed using the intelligent temperature control module to generate the first prediction information.

[0087] After introducing the basic principles of this application, various non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0088] Example 1

[0089] like Figure 1 As shown, this application provides a method for predicting temperature and thermal management energy consumption based on navigation charging. The method is applied to a prediction system for temperature and thermal management energy consumption based on navigation charging. The system is communicatively connected to a BMS (Battery Management System), and the BMS includes a SOC (State of Charge) module, a remaining time module, and an intelligent temperature control module. The method specifically includes the following steps:

[0090] Step S100: Calculate the BMS of the first vehicle in the power-on update state according to the SOC module, and send the first cycle information;

[0091] Specifically, the SOC module is a module for calculating the state of charge (SOC) of the battery, wherein the SOC refers to a state of charge parameter of the battery. The first vehicle is a new energy vehicle. The power-on update state is a state of the vehicle in a power-on timing after power-on. The first period information refers to BMS calculated by the SOC module in the power-on update state of the vehicle, and specifically includes: current available energy, 80% SOC available energy, safe energy, and energy corresponding to a user-set destination SOC. The BMS in the power-on update state is obtained, thereby providing basic data for subsequent prediction of the temperature and thermal management energy consumption of the first vehicle in a navigation state.

[0092] Preferably, the current available energy is the available energy of the current state of the power battery, the 80% SOC available energy is 80%*maximum available energy at the current temperature, the safe energy is 20%*maximum available energy at the current temperature, and the energy corresponding to the user-set destination SOC is user-set destination SOC / conversion factor*maximum available energy at the current temperature.

[0093] Step S200: Real-time collection of a first state of the first vehicle, and determination of whether the first state conforms to a first preset navigation state, wherein the first preset navigation state is a set navigation state in a navigation state.

[0094] Specifically, the first state refers to a vehicle control state of the first vehicle at a current time. The first state of the first vehicle is collected in real time, and it is determined whether the vehicle is in the first preset navigation state. The first preset navigation state is a set navigation state in a navigation state. It is determined whether the vehicle starts navigation and is ready to reach the next station or destination, thereby achieving the technical effect of laying a foundation for subsequent management of charging of the vehicle based on navigation.

[0095] Step S300: If the first state conforms to the first preset navigation state, collecting a first route station selection plan, and determining whether the first vehicle is currently performing station selection according to the first route station selection plan.

[0096] Specifically, it is determined whether the first vehicle is in a state of starting navigation and being ready to reach the next station or destination, the first route station selection plan is collected, and it is determined whether the first vehicle is currently performing station selection according to whether there is a station selection flag in the first route station selection plan. The first route station selection plan is plan information of a route and station selection of the user when setting vehicle navigation information. Thus, the technical effect of providing basic data for subsequent further analysis of the state of the first vehicle is achieved.

[0097] Step S400: If the first vehicle is currently in the process of selecting a pile, the first period information is calculated and updated by using the SOC module and the remaining time module to obtain second period information;

[0098] Specifically, it is judged that the first vehicle is currently in the process of selecting a pile, which indicates that the first vehicle has a demand for charging. Therefore, the first period information is calculated and updated by using the SOC module and the remaining time module to obtain the second period information. The second period information is the BMS of the first vehicle in the state of pile selection calculation, including the remaining SOC of each pile, the SOC of reaching the destination when there is a planned pile, and the charging time of each pile. The remaining time module is a calculation module of the charging time calculated according to the slow charging remaining time. The technical effect of improving the vehicle operation stability and reliability is achieved by reliably predicting the temperature and thermal management energy consumption during charging according to different states of the first vehicle.

[0099] Preferably, the remaining SOC of reaching each pile is the remaining SOC (SOCDOWN) of reaching the jth pile, where j is a positive integer greater than or equal to 2. The SOC of reaching the destination when there is a planned pile is the SOC of reaching the destination when there are i planned piles, and i is a positive integer greater than or equal to 1. The charging time of each pile is the charging time calculated according to the slow charging remaining time when the maximum charging capacity of the charging pile is less than 20A.

[0100] Step S500: Real-time collection and update of the first state to obtain a second state, and judging whether the second state conforms to a second preset navigation state, wherein the second preset navigation state is a start navigation state in a navigation state;

[0101] Specifically, the second state is the state of the first vehicle obtained by real-time collection and update of the first state. The judgment of whether the second state conforms to the second preset navigation state is used to judge whether the first vehicle has started to depart for the destination or plan a pile. The second preset navigation state is a start navigation state in a navigation state. Therefore, the technical effect of laying a foundation for further analysis and prediction of the temperature and thermal management energy consumption of the first vehicle when reaching the destination is achieved.

[0102] Step S600: If the second state conforms to the second preset navigation state, the second period information is calculated and updated by using the SOC module and the remaining time module to obtain third period information;

[0103] Specifically, if the second state matches the second preset navigation state, it indicates that the first vehicle starts to navigate to a destination. The second period information is calculated and updated by the SOC module and the remaining time module to obtain third period information. The third period information is the BMS of the first vehicle in the starting navigation state, including the remaining SOC of the next stake in navigation or the remaining SOC to the destination, the charging cutoff SOC of the next stake in navigation, and the charging time of the next stake in navigation. The BMS of the first vehicle in the starting navigation state is obtained, and the technical effect of further improving the accuracy of predicting the temperature and thermal management energy consumption of the charging is achieved.

[0104] Preferably, the remaining SOC of the next stake in navigation or the remaining SOC to the destination is the remaining SOC to each stake. The charging cutoff SOC of the next stake in navigation is the upper limit of the charging SOC. The charging time of the next stake in navigation is the charging time calculated according to the slow charging remaining time when the maximum charging capacity of the next charging stake is <20A during navigation.

[0105] Step S700: analyzing the third period information by using the intelligent temperature control module to generate first prediction information.

[0106] Specifically, the intelligent temperature control module refers to a module for analyzing and predicting the temperature and battery thermal management energy consumption. The first prediction information refers to the battery temperature and thermal management energy consumption information predicted by analyzing the information obtained based on the navigation state of the first vehicle. Thus, the temperature and thermal management energy consumption are predicted in real time based on the user navigation information, intelligent and accurate navigation planning is provided for user navigation, the accuracy of navigation is improved, and the technical effect of improving the stability and service life of automobile operation is achieved.

[0107] Further, as shown in Figure 2 If the first state matches the first preset navigation state, the first route selection stake planning is collected before the step 300 of the embodiment of the application further includes:

[0108] If the first state matches the first preset navigation state, the first period information is calculated and updated by using the SOC module to obtain fourth period information.

[0109] The fourth period information refers to the BMS of the first vehicle in the setting navigation state, and the fourth period information is calculated by the SOC module.

[0110] Specifically, when the first vehicle is in a start navigation state, the first period information is updated by the SOC module to obtain the fourth period information. The fourth period information refers to the BMS of the first vehicle in a set navigation state. The fourth period information includes: SOC of reaching the destination without selecting a pile, and remaining SOC after returning. Thus, the SOC of reaching the destination and the remaining SOC after returning can be obtained without planning to charge in the middle, thereby better planning the navigation of the first vehicle.

[0111] Specifically, the fourth period information is calculated by the SOC module and includes:

[0112] The calculation formula of the SOC (SOCE) of reaching the destination without selecting a pile is:

[0113] SOCE = SOC0 - ΔSOC

[0114] Wherein, ΔSOC is the road consumption SOC of reaching the destination, which is obtained by converting the road consumption energy.

[0115] The calculation formula of the remaining SOC (SOCEE) after returning is:

[0116] SOCEE = SOC0 - 2*ΔSOC

[0117] Wherein, SOC0 is the initial SOC.

[0118] Further, as shown in the SOC module and the remaining time module, the first period information is updated to obtain the second period information, and the step S400 of the embodiment of the application further includes: Figure 2

[0119] Step S410: calculating the BMS of the first vehicle by the SOC module to obtain the first information;

[0120] Step S420: calculating the BMS of the first vehicle by the remaining time module to obtain the second information;

[0121] Step S430: according to the first information and the second information, the second period information is composed, wherein the second period information refers to the BMS of the first vehicle in the selected pile calculation state.

[0122] ​Specifically, the first information is the remaining SOC upon reaching each charging station and the SOC upon reaching the destination when there are planned charging stations; the second information is the charging time for each charging station. Through the SOC module and the remaining time module, the SOC and charging time information can be accurately calculated, achieving the technical effect of providing accurate data for subsequent analysis of the battery temperature and thermal management energy consumption of the first vehicle.

[0123] Specifically, this also includes obtaining the remaining SOC (Sodium Calibration) reaching each stake. j The calculation process of ) is as follows:

[0124] Remaining SOC for the first charging station:

[0125] SOCDOWN1=SOC0-ΔSOC1

[0126] The remaining SOC of the j-th (2≤j≤i) charging pile

[0127] (SOCDOWN j ) = min(SOCUP j-1 -ΔSOC j )

[0128] Wherein, ΔSOC j The SOC consumed by the j-th segment.

[0129] Calculate the upper limit of charging SOC (SOCUP) j :

[0130] i represents the number of charging stations selected. When the charging station is not the last charging station (i.e., the j-th station, j≤i-1):

[0131] SOCUP j =min(ΔSOC) j+1 +20%, 100%

[0132] Wherein, ΔSOC j+1 For the road consumption SOC after passing the j-th charging pile, the last charging pile, i.e., j=i:

[0133] [SOCUP j =minΔSOC j+1 +max(20%, user-defined SOC), 100%]

[0134] The formula for calculating the State of Charge (SOC) upon reaching the destination when there are planned stakes is as follows:

[0135] SOCE = SOCUP j＝i -ΔSOC j＝i+1

[0136] Where i represents the number of planned stakes, and 1 ≤ j ≤ i.

[0137] The calculation formula for obtaining the charging time of each pile is:

[0138] The remaining charging time t(i) of the i-th pile is:

[0139] t(i) = t[min(SOCSET, SOCUP i )] - t(SOCDOWN i ),

[0140] Wherein, SOCSET is the user-set SOC.

[0141] Further, as shown in Figure 3 the embodiment of the present application, after the second period information is composed according to the first information and the second information, step S430 further includes:

[0142] Step S431: analyzing the second period information by using the intelligent temperature control module to obtain a first analysis result;

[0143] Step S432: generating second prediction information according to the first analysis result, wherein the second prediction information includes the prediction of the temperature and thermal management energy consumption of the first vehicle in the selected pile calculation state.

[0144] Specifically, the first analysis result includes the temperature prediction value of each pile and the battery thermal management energy consumption of each section of road. The second prediction information includes the prediction of the temperature and thermal management energy consumption of the first vehicle in the selected pile calculation state. Thus, the vehicle battery temperature and thermal management energy consumption in the selected pile calculation state are obtained, and the technical effect of improving the prediction accuracy is achieved.

[0145] Specifically, the analysis of the second period information by using the intelligent temperature control module further includes obtaining the calculation and analysis process of the temperature prediction value of each pile:

[0146] If the remaining SOC of the planned charging pile is > 20%, the environmental temperature is ≤ 15℃, and the battery temperature of the charging pile is 20℃;

[0147] If the remaining SOC of the planned charging pile is > 20%, the environmental temperature is > 15℃, and the battery temperature of the charging pile is 30℃;

[0148] If the remaining SOC of the planned charging pile is 0 < SOC < 20%, the environmental temperature is ≤ 15℃, and the battery thermal management energy consumption is ≤ 0, the battery temperature of the charging pile is 20℃;

[0149] If the remaining SOC is 0<SOC<20% when arriving at the planned charging pile, the ambient temperature is ≤15℃, and the power battery thermal management energy consumption is >0, then the battery temperature when arriving at the charging pile is:

[0150]

[0151] If the remaining SOC is 0<SOC<20% when arriving at the planned charging pile, the ambient temperature is >15℃, and the power battery thermal management energy consumption is >0, then the battery temperature when arriving at the charging pile is:

[0152]

[0153] If the remaining SOC is ≤0 when arriving at the planned charging pile, then the battery temperature when arriving at the charging pile is:

[0154]

[0155] Specifically, the analysis of the second period information by the intelligent temperature control module further includes obtaining a calculation and analysis process of the battery thermal management energy consumption of each section of road:

[0156] Predicted heating starting battery temperature Theatstart:

[0157]

[0158] Predicted cooling starting temperature Tcoolstart:

[0159]

[0160] wherein Tbatmin is the minimum battery temperature, Tbatmax is the maximum battery temperature, k is the temperature drop coefficient per unit time, unit: 1 / min, R is the total internal resistance of the battery system, C is the specific heat capacity of the battery system, w i is the energy consumption of each section of road, t i is the predicted driving time of each section of road.

[0161] If the maximum capacity of the charging pile is >20A, then:

[0162] 1) Predicted time required for heating:

[0163] Theatstart<-20℃

[0164]

[0165] -20℃≤Theatstart<0℃

[0166]

[0167] 0℃≤Theatstart<20℃

[0168] t h =(T2-Theatstart) / v h2

[0169] 20℃≤Theatstart<32℃

[0170] t h =0

[0171] Among them, T i v is the temperature at the breakpoint. hi For T i -T i-1 The corresponding temperature rise rate, v h0 The temperature rise rate is the rate at which the temperature is less than T1, T3 = 20℃ (fast charging stop heating threshold), T2 = 0℃, T1 = -20℃.

[0172] 2) Predict the cooling time required

[0173] Tcoolstart > 55℃

[0174]

[0175] 40℃≤Tcoolstart<55℃

[0176]

[0177] 32℃≤Tcoolstart<40℃

[0178] t c =(T2-T0) / v c2

[0179] 20℃≤Tcoolstart<32℃

[0180] t c =0

[0181] Among them, T i v is the temperature at the breakpoint. ci For T i -T i-1 The corresponding cooling rate, v h0 The cooling rate corresponding to a temperature greater than T1 is given by T3 = 32℃ (fast charging stop heating threshold), T2 = 40℃, and T1 = 55℃.

[0182] 3) Predicting the power consumption of thermal management

[0183] Wthermal(i) = t hi *P hi +t ci *Pci

[0184] where P h is the heating power, P c is the cooling power

[0185] 4) Predicting thermal management benefit electricity

[0186]

[0187] where T is the minimum temperature of the monomer, signed, 0.5 is the capacity attenuation ratio of -30℃, and E is the nominal electricity corresponding to 1C * SOH.

[0188] When Theatstart≥25℃, the benefit electricity is 0.

[0189] 5) Calculate the cumulative sum of thermal management energy consumption and benefit electricity (thermal management energy consumption)

[0190] W=Wthermal(i)+Wwearing(i)

[0191] Referring to Figure 4 Further, the step S600 of the embodiment of the application further comprises:

[0192] Step S610: If the second state does not conform to the second preset navigation state, a first judgment instruction is obtained.

[0193] Step S620: According to the first judgment instruction, the selection of the pile of the first vehicle is judged.

[0194] Step S630: If the first vehicle fails to select the pile, a first reminding instruction is obtained.

[0195] Specifically, when the first vehicle is not in the starting navigation state, the selection of the pile of the first vehicle is judged according to the first judgment instruction. If the judgment result is that the first vehicle fails to select the pile, the first reminding instruction is obtained. The first reminding instruction refers to reminding the user to select the charging pile. Thus, the technical effect of improving the accuracy of navigation and reliably managing the battery condition of the vehicle is achieved.

[0196] Referring to Figure 5 Further, the step S600 of the embodiment of the application further comprises:

[0197] Step S640: The BMS of the first vehicle is calculated by using the SOC module to obtain third information.

[0198] Step S650: Calculate the BMS of the first vehicle using the remaining time module to obtain the fourth information;

[0199] Step S660: Based on the third information and the fourth information, form the third cycle information, wherein the third cycle information refers to the BMS of the first vehicle in the navigation start state.

[0200] Specifically, the third information is calculated using the SOC module to determine the BMS of the first vehicle, including: the remaining SOC at the next charging station during navigation or the remaining SOC upon reaching the destination, and the SOC at the charging cutoff point for the next charging station during navigation. The fourth information is calculated using the remaining time module to determine the BMS of the first vehicle, including: the charging time for the next charging station during navigation. This achieves the technical effect of obtaining the BMS of the first vehicle in the navigation start state, providing analytical data for subsequent analysis and prediction of the temperature and thermal management energy consumption of the first vehicle in the navigation start state.

[0201] Specifically, the step of using the SOC module to calculate the BMS of the first vehicle and obtain the third information also includes obtaining a formula for the remaining SOC of the next marker in the navigation or the remaining SOC upon reaching the destination:

[0202] SOCDOWN1=SOC0-ΔSOC1

[0203]

[0204] Formula for obtaining the charging cutoff SOC of the next charging station in the navigation:

[0205]

[0206] SOCUP j＝i =min[ΔSOC] j+1 +max(20%, user-defined SOC), 100%]

[0207] Specifically, the step of using the remaining time module to calculate the BMS of the first vehicle and obtain the fourth information also includes obtaining a formula for the charging time of the next charging station in the navigation:

[0208] The remaining charging time t(i) for the i-th charging pile:

[0209] t(i)=t[min(SOCSET,SOCUP i )]-t(SOCDOWN i )

[0210] SOCCSET is used to set the SOC for the user.

[0211] Referring to Figure 6 Further, after the third periodic information is composed according to the third information and the fourth information, the step S660 of the embodiment of the application further includes:

[0212] Step S661: analyzing the third periodic information by using the intelligent temperature control module to obtain a second analysis result.

[0213] Step S662: generating the first prediction information according to the second analysis result, wherein the first prediction information includes a prediction of the temperature and thermal management energy consumption of the first vehicle in a starting navigation state.

[0214] Specifically, the second analysis result is the battery temperature reaching the next stake, and the thermal management energy consumption of the vehicle reaching the next charging stake. According to the second analysis result, the first prediction information is generated to obtain a prediction result of the temperature and thermal management energy consumption of the first vehicle in a starting navigation state, and then the battery management of the first vehicle can be changed according to the prediction result, including charging time change and thermal management change. The charging time change refers to that, under the condition of not being fully charged, the remaining time calculation does not use the voltage formula. Thus, the real-time prediction of the temperature and thermal management energy consumption of the vehicle can be realized, thereby achieving the technical effect of better navigation planning of the vehicle.

[0215] Specifically, the step of analyzing the third periodic information by using the intelligent temperature control module to obtain a second analysis result further includes:

[0216] 1) obtaining an analysis process of the battery temperature reaching the next stake:

[0217] If the remaining SOC reaching the planned charging stake is greater than 20%, and the environmental temperature is less than or equal to 15℃, then the battery temperature reaching the charging stake is 20℃.

[0218] If the remaining SOC reaching the planned charging stake is greater than 20%, and the environmental temperature is greater than 15℃, then the battery temperature reaching the charging stake is 30℃.

[0219] If the remaining SOC reaching the planned charging stake is 0<SOC<20%, the environmental temperature is less than or equal to 15℃, and the thermal management energy consumption of the power battery is 0, then the battery temperature reaching the charging stake is 20℃.

[0220] If the remaining SOC reaching the planned charging stake is 0<SOC<20%, the environmental temperature is less than or equal to 15℃, and the thermal management energy consumption of the power battery is greater than 0, then the battery temperature reaching the charging stake is:

[0221]

[0222] When the remaining SOC is 0 < SOC < 20% and the ambient temperature is > 15℃ and the thermal management energy consumption is > 0 when the vehicle arrives at the planned charging pile, the battery temperature when the vehicle arrives at the charging pile is:

[0223]

[0224] When the remaining SOC is ≤ 0 when the vehicle arrives at the planned charging pile, the battery temperature when the vehicle arrives at the charging pile is:

[0225]

[0226] 2) Obtain an analysis formula of the thermal management energy consumption of the vehicle arriving at the next charging pile:

[0227] W = Wthermal(i) + Wwearing(i)

[0228] Specifically, the thermal management change further includes:

[0229] 1) When all the following conditions are met, heating is turned on:

[0230] ① When the remaining time of the vehicle traveling to the pile is less than 1.1 * the heating time required;

[0231] ② When the minimum battery temperature is ≤ the minimum heating threshold Thmin;

[0232] ③ The temperature difference is ≤ the temperature difference setting threshold (20℃);

[0233] ④ The ambient temperature is ≤ 20℃;

[0234] ⑤ In one discharging process, the WTC (or WTC_B) power consumption when heating is turned on is ≤ 0.045 * E (kwh) (calculated from the end of charging, E is the nominal electric quantity);

[0235] ⑥ The current vehicle speed is > 2km / h (excluding vehicle stop);

[0236] ⑦ The current SOC is > 2%.

[0237] 2) When any of the following conditions is met, heating is stopped:

[0238] ① When the minimum battery temperature is > the maximum heating threshold Thmax;

[0239] ② The temperature difference is > the temperature difference setting threshold 2 (20℃);

[0240] ③ The ambient temperature is > 20℃;

[0241] ④ In one discharging process, the WTC (or WTC_B) power consumption when heating is turned on is > 0.045 * E (kwh) (calculated from the end of charging, E is the nominal electric quantity);

[0242] ⑤The average vehicle speed in the last 10 minutes is less than or equal to 2 km / h;

[0243] ⑥SOC is less than or equal to 2%;

[0244] ⑦The cumulative discharge ampere-hours after charging is greater than the nominal capacity*SOH (the nominal capacity corresponding to 1C);

[0245] ⑧2% < SOC is less than or equal to 20% and the predicted WTC consumption / revenue power is greater than 1, that is, ET is the average consumption power (kwh / ℃) of the last 5℃ temperature rise or the average consumption power in the last 15 minutes (the calculation starts when the battery minimum temperature rise is greater than or equal to 7℃ after the heating is turned on), the initial value is 0, E is the nominal power*SOH corresponding to 1C, the initial value is 0, and 0.5 is the capacity attenuation ratio at -30℃ (the calibrated quantity).

[0246] 3) Heating recovery when all the following conditions are met:

[0247] ①When the battery minimum temperature is less than or equal to the heating minimum threshold Thmin;

[0248] ②The temperature difference is less than or equal to the temperature difference setting threshold (20℃);

[0249] ③The ambient temperature is less than or equal to 20℃;

[0250] ④During a discharge process, the WTC (or WTC_B) power consumption when the heating is turned on is less than or equal to 0.045*E (kwh) (calculated from the end of charging, E is the nominal power);

[0251] ⑤The average vehicle speed in the last 10 minutes is greater than 2 km / h;

[0252] ⑦The cumulative discharge ampere-hours after charging is less than the nominal capacity*SOH (the nominal capacity corresponding to 1C).

[0253] 4) Cooling start point judgment

[0254] ⑧The current SOC is greater than 20% or the current 2% < SOC is less than or equal to 20% and the predicted WTC consumption / revenue power is less than 1, that is, ET is the average consumption power (kwh / ℃) of the last 5℃ temperature rise or the average consumption power in the last 15 minutes (the calculation starts when the battery minimum temperature rise is greater than or equal to 7℃ after the heating is turned on), the initial value is 0, E is the nominal power*SOH corresponding to 1C, the initial value is 0, and 0.5 is the capacity attenuation ratio at -30℃ (the calibrated quantity).

[0255] 5) Inlet temperature control after heating is turned on

[0256]

[0257]

[0258] Tinput temperature range is between [28, 45].

[0259] Wherein, f(x) is the mileage retention rate at different temperatures; V is the vehicle speed, the initial value V0=28, the average speed in the last 10 minutes, VT is the recent 5℃ temperature rise rate, the initial value of VT is 15; R0 is the nominal mileage; SOC is the SOC based on the normal temperature capacity.

[0260] 6) High-temperature power battery cooling control

[0261] If the ambient temperature is ≥20℃, according to the battery cell temperature of the vehicle before departure, the remaining time when the vehicle drives to the pile, and the battery temperature rise rate under the working condition, it is calculated whether the temperature of the power battery will reach the cell temperature threshold of driving refrigeration before the vehicle drives to the pile;

[0262] ①If it is estimated that the vehicle will not reach the cell temperature threshold of driving refrigeration before driving to the pile, the estimated refrigeration consumption energy is 0.

[0263] ②If it is estimated that the vehicle will reach the cell temperature threshold of driving refrigeration before driving to the pile, according to the estimated time point of starting refrigeration of the vehicle, the remaining time when the vehicle drives to the pile, and the battery temperature drop rate when the driving refrigeration is started, the time t1 required for battery refrigeration is calculated, so as to estimate the energy E consumed by refrigeration = P 制冷 *t1;

[0264] The energy consumed by refrigeration of each subsequent section is estimated: assuming that the maximum temperature of the cell after each fast charging is 30℃, then repeat ① and ② to estimate the energy consumed by refrigeration of each section.

[0265] In summary, the temperature and thermal management energy consumption prediction method based on navigation charging provided by the application has the following technical effects:

[0266] 1. The application calculates the BMS of the first vehicle in the power-on update state, sets the navigation state, and starts the navigation state through the SOC module and the remaining time module, judges whether the first vehicle is currently selecting the pile; if selecting the pile, the first cycle information is calculated and updated to obtain the second cycle information; if in the starting navigation state, the third cycle information is obtained; the intelligent temperature control module is used to analyze the third cycle information to generate the first prediction information. The technical effects of accurately predicting the temperature and thermal management energy consumption based on navigation information are realized, thereby improving the accuracy of navigation, improving the stability and service life of automobile operation.

[0267] 2. When the first vehicle is in a start navigation state, the first period information is calculated and updated by the SOC module to obtain fourth period information. The fourth period information refers to the BMS of the first vehicle in a set navigation state. The fourth period information includes the SOC of reaching the destination without selecting a pile and the remaining SOC of returning. Thus, the SOC of reaching the destination and the remaining SOC after returning can be obtained without planning to charge in the middle, thereby achieving the technical effect of better planning the navigation of the first vehicle.

[0268] 3. The BMS of the first vehicle is calculated by the remaining time module to obtain second information. The second information is composed of the first information and the second information, and the second period information refers to the BMS of the first vehicle in a selected pile calculation state. The SOC and charging time information can be accurately calculated by the SOC module and the remaining time module, thereby achieving the technical effect of providing accurate data for subsequent analysis of the battery temperature and thermal management energy consumption of the first vehicle.

[0269] Embodiment two

[0270] Based on the same inventive concept as the above-mentioned embodiment, the present application also provides a prediction system for temperature and thermal management energy consumption based on navigation charging, as shown in Figure 7 The system comprises:

[0271] A first sending unit 11 is configured to calculate the BMS of the first vehicle in a power-on update state according to the SOC module, and send first period information.

[0272] A first judging unit 12 is configured to collect the first state of the first vehicle in real time, and judge whether the first state meets a first preset navigation state. The first preset navigation state is a set navigation state in a navigation state.

[0273] A second judging unit 13 is configured to collect first route pile selection planning if the first state meets the first preset navigation state, and judge whether the first vehicle is currently selecting a pile according to the first route pile selection planning.

[0274] A first obtaining unit 14 is configured to calculate and update the first period information by the SOC module and the remaining time module to obtain second period information if the first vehicle is currently selecting a pile.

[0275] A third judging unit 15 is configured to collect the first state in real time, obtain a second state, and judge whether the second state conforms to a second preset navigation state, wherein the second preset navigation state is a start navigation state in a guiding navigation state.

[0276] A second obtaining unit 16 is configured to, if the second state conforms to the second preset navigation state, calculate and update the second period information by using the SOC module and the remaining time module, and obtain third period information.

[0277] A first generating unit 17 is configured to analyze the third period information by using an intelligent temperature control module, and generate first prediction information.

[0278] Further, the system further comprises:

[0279] A third obtaining unit is configured to, if the first state conforms to the first preset navigation state, calculate and update the first period information by using the SOC module, and obtain fourth period information.

[0280] A first setting unit is configured to set the fourth period information, wherein the fourth period information refers to a BMS of the first vehicle in a set navigation state, and the fourth period information is calculated by the SOC module.

[0281] Further, the system further comprises:

[0282] A fourth obtaining unit is configured to calculate the BMS of the first vehicle by using the SOC module, and obtain first information.

[0283] A fifth obtaining unit is configured to calculate the BMS of the first vehicle by using the remaining time module, and obtain second information.

[0284] A first composing unit is configured to compose the second period information according to the first information and the second information, wherein the second period information refers to the BMS of the first vehicle in a selected calculation state.

[0285] Further, the system further comprises:

[0286] A sixth obtaining unit is configured to analyze the second period information by using the intelligent temperature control module, and obtain a first analysis result.

[0287] The second generating unit is configured to generate second prediction information according to the first analysis result, wherein the second prediction information comprises a prediction of the temperature and thermal management energy consumption of the first vehicle in the selected computing state.

[0288] Further, the system further comprises:

[0289] The seventh obtaining unit is configured to obtain a first judgment instruction if the second state does not conform to the second preset navigation state.

[0290] The fourth judgment unit is configured to judge the selected computing state of the first vehicle according to the first judgment instruction.

[0291] The eighth obtaining unit is configured to obtain a first reminding instruction if the first vehicle fails to be selected.

[0292] Further, the system further comprises:

[0293] The ninth obtaining unit is configured to obtain third information by calculating the BMS of the first vehicle by using the SOC module.

[0294] The tenth obtaining unit is configured to obtain fourth information by calculating the BMS of the first vehicle by using the remaining time module.

[0295] The second composing unit is configured to compose the third periodic information according to the third information and the fourth information, wherein the third periodic information refers to the BMS of the first vehicle in the starting navigation state.

[0296] Further, the system further comprises:

[0297] The eleventh obtaining unit is configured to obtain a second analysis result by analyzing the third periodic information by using the intelligent temperature control module.

[0298] The third generating unit is configured to generate the first prediction information according to the second analysis result, wherein the first prediction information comprises a prediction of the temperature and thermal management energy consumption of the first vehicle in the starting navigation state.

[0299] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. Figure 1The method for predicting temperature and thermal management energy consumption based on navigation charging in embodiment one and the specific example are also applicable to the system for predicting temperature and thermal management energy consumption based on navigation charging in the present embodiment. Those skilled in the art can clearly understand the system for predicting temperature and thermal management energy consumption based on navigation charging in the present embodiment through the foregoing detailed description of the method for predicting temperature and thermal management energy consumption based on navigation charging. Therefore, for the sake of brevity of the description, no further detailed description is given herein. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant part is described in the method part.

[0300] The foregoing description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0301] Exemplary electronic device

[0302] The electronic device of the present application is described below with reference to Figure 8

[0303] Based on the same inventive concept as the method for predicting temperature and thermal management energy consumption based on navigation charging in the foregoing embodiments, the present application also provides a system for predicting temperature and thermal management energy consumption based on navigation charging, comprising: a processor coupled with a memory, the memory being used to store a program, when the program is executed by the processor, the system is caused to perform the steps of the method described in embodiment one.

[0304] The electronic device 300 comprises a processor 302, a communication interface 303, and a memory 301. Optionally, the electronic device 300 can further comprise a bus architecture 304. The communication interface 303, the processor 302, and the memory 301 can be connected with each other through the bus architecture 304. The bus architecture 304 can be a peripheral component interconnect (PCI) bus or an extended industry Standard Architecture (EISA) bus, etc. The bus architecture 304 can be divided into an address bus, a data bus, a control bus, etc. For the sake of brevity of the description, Figure 6 In the figure, only one thick line is used to represent the bus architecture 304, but it does not mean that there is only one bus or only one type of bus.

[0305] ​The processor 302 can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of programs of the present application.

[0306] The communication interface 303, using any transceiver-like device, is used to communicate with other devices or communication networks, such as an Ethernet, a radio access network (RAN), a wireless local area network (WLAN), a wired access network, etc.

[0307] The memory 301 can be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage or other magnetic storage devices, or any other medium capable of storing desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to this. The memory can exist independently and be connected to the processor through the bus architecture 304. The memory can also be integrated with the processor.

[0308] The memory 301 is used to store computer execution instructions for executing the programs of the present application, and the processor 302 is used to control the execution. The processor 302 is used to execute the computer execution instructions stored in the memory 301, thereby realizing the navigation charging-based temperature and thermal management energy consumption prediction method provided by the above-mentioned embodiments of the present application.

[0309] Those skilled in the art can understand that the various numbers such as first, second, etc. involved in the present application are only for the convenience of description and do not limit the scope of the present application, nor indicate the order of precedence. The association relationship of the associated objects described by "and / or" indicates that there can be three kinds of relationships, for example, A and / or B can represent the existence of A alone, the existence of A and B together, and the existence of B alone. The character " / " generally represents an "or" relationship between the associated objects before and after it. "At least one" means one or more. At least two means two or more. "At least one", "any one" or similar expressions mean any combination of these items, including any combination of single item or multiple items. For example, at least one of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0310] In the above embodiments, all or part can be realized by software, hardware, firmware, or any combination thereof. When realized by software, all or part can be realized in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, the computer program instructions produce all or part of the processes or functions described in the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be magnetic media (such as floppy disk, hard disk, magnetic tape), optical media (such as DVD), or semiconductor media (such as solid state disk (SSD)) and the like.

[0311] The steps of a method or algorithm described in connection with the present disclosure can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is tangible and can be accessed by a processor. The storage medium can be part of the processor, part of memory (including memory shared with a processor) or be stored in another location (e.g., a remote computer or a hard disk drive that can be used as a computer system storage, etc.) that can be accessed by the processor. The processor can access information stored in the storage medium through any computer type of media that can be accessed by a processor. Figure 1 one or more processes and / or blocks Figure 1 one or more blocks or steps of a method or algorithm.

[0312] Furthermore, reference numerals can be repeated in different examples of the present disclosure. Such repetition is for the purpose of simplicity and clarity and does not itself dictate a relationship between the various embodiments and / or configurations discussed.

[0313] It is also important to note that while the above describes example embodiments, there are several variations and modifications which can be made to them without departing from the scope of the present disclosure. For example, the order or sequence of any process steps can be varied or re-sequenced without departing. Moreover, other operations dealing with objects can be performed or utilized. Accordingly, the appended claims are intended to cover all such variations and modifications as falling within the scope of the present disclosure.

[0314] The preferred embodiments of the present disclosure have been described above with the aid of numerous reference numbers. It is to be understood that the above description is intended to come within the scope of the appended claims and that changes and modifications can be made by those skilled in the art without departing from the spirit of the present disclosure.

Claims

1. A method for predicting temperature and thermal management energy consumption based on navigation charging, characterized in that, The method is applied to a navigation-based charging temperature and thermal management energy consumption prediction system, the system is in communication connection with a battery management system (BMS), and the BMS comprises a power battery state of charge (SOC) module, a remaining time module and an intelligent temperature control module, and the method comprises: According to the SOC module, the BMS information of the first vehicle in the power-on update state is calculated, and first cycle information is sent, the first cycle information comprising at least one of the following: the current available energy of the first vehicle, the available energy at 80% SOC, the safety power, and the energy corresponding to the user-set destination SOC; The first state of the first vehicle is collected in real time, and it is judged whether the first state conforms to the first preset navigation state, wherein the first preset navigation state is a set navigation state in a navigation state; If the first state conforms to the first preset navigation state, a first route and pile selection planning is collected, and it is judged whether the first vehicle is currently performing pile selection according to the first route and pile selection planning, the first route and pile selection planning being the planned information of the route and pile selection when the user sets the vehicle navigation information; If the first vehicle is currently performing pile selection, the first cycle information is calculated and updated by using the SOC module and the remaining time module, and second cycle information is obtained, the second cycle information comprising the remaining SOC to each pile, the SOC to the destination when there is a planned pile, and the charging time of each pile; The first state is collected in real time, and a second state is obtained, and it is judged whether the second state conforms to a second preset navigation state, wherein the second preset navigation state is a start navigation state in a navigation state; If the second state conforms to the second preset navigation state, the second cycle information is calculated and updated by using the SOC module and the remaining time module, and third cycle information is obtained, the third cycle information comprising the remaining SOC to the next pile in navigation or the remaining SOC to the destination, the charging cutoff SOC of the next pile in navigation, and the charging time of the next pile in navigation; The third cycle information is analyzed by using the intelligent temperature control module, and first prediction information is generated, the first prediction information comprising the battery temperature and thermal management energy consumption information of the first vehicle.

2. The method of claim 1, wherein, The method further comprises: If the first state conforms to the first preset navigation state, the first cycle information is calculated and updated by using the SOC module, and fourth cycle information is obtained; The fourth cycle information is the BMS information of the first vehicle in the set navigation state, and the fourth cycle information is calculated by the SOC module.

3. The method of claim 1, wherein, The method further comprises: calculating BMS information of the first vehicle by using the SOC module to obtain first information, the first information including at least one of the following: a remaining SOC of the first vehicle to reach each pole and a SOC of the first vehicle to reach a destination when a planned pole is reached; calculating BMS information of the first vehicle by using the remaining time module to obtain second information, the second information including a charging time of each pole; composing the second period information according to the first information and the second information, wherein the second period information refers to BMS information of the first vehicle in a pole selection calculation state.

4. The method of claim 3, wherein, After composing the second period information according to the first information and the second information, the following includes: analyzing the second period information by using the intelligent temperature control module to obtain a first analysis result, the first analysis result including a temperature prediction value of the first vehicle to reach each pole and battery thermal management energy consumption of each section of road; generating second prediction information according to the first analysis result, wherein the second prediction information includes a prediction of temperature and thermal management energy consumption of the first vehicle in the pole selection calculation state.

5. The method of claim 1, wherein, The judging whether the second state conforms to the second preset navigation state further includes: if the second state does not conform to the second preset navigation state, obtaining a first judgment instruction, the first judgment instruction being used to indicate whether the first vehicle is successful in pole selection; judging a pole selection condition of the first vehicle according to the first judgment instruction; if the first vehicle is not successful in pole selection, obtaining a first reminding instruction.

6. The method of claim 1, wherein, The calculating and updating the second period information by using the SOC module and the remaining time module to obtain third period information includes: calculating BMS information of the first vehicle by using the SOC module to obtain third information, the third information including at least one of the following: a remaining SOC of a next pole in navigation or a remaining SOC to reach a destination, a charging cutoff SOC of the next pole in navigation; calculating BMS information of the first vehicle by using the remaining time module to obtain fourth information, the fourth information including a charging time of the next pole in navigation; composing the third period information according to the third information and the fourth information, wherein the third period information refers to BMS information of the first vehicle in a start navigation state.

7. The method of claim 6, wherein, After composing the third period information according to the third information and the fourth information, the following includes: analyzing the third period information by using the intelligent temperature control module to obtain a second analysis result, the second analysis result including a battery temperature to reach the next pole and thermal management energy consumption of the vehicle to reach the next charging pole; generating the first prediction information according to the second analysis result, wherein the first prediction information includes a prediction of temperature and thermal management energy consumption of the first vehicle in the start navigation state.

8. A system for predicting temperature and thermal management energy consumption based on navigation charging, characterized in that, The system includes: The first sending unit is configured to calculate BMS information of the first vehicle in a power-on updating state according to an SOC module, and send first periodic information, the first periodic information including at least one of the following: current available energy of the first vehicle, available energy at 80% SOC, safe energy, and energy corresponding to a user-set destination SOC; The first judging unit is configured to collect a first state of the first vehicle in real time, and determine whether the first state conforms to a first preset navigation state, wherein the first preset navigation state is a set navigation state in a guide navigation state; The second judging unit is configured to, if the first state conforms to the first preset navigation state, collect first route and pile selection planning, and determine whether the first vehicle is currently performing pile selection according to the first route and pile selection planning, the first route and pile selection planning being planned information of a route and pile selection when a user sets vehicle navigation information; The first obtaining unit is configured to, if the first vehicle is currently performing pile selection, update the first periodic information by using the SOC module and a remaining time module, and obtain second periodic information, the second periodic information including remaining SOC to each pile, SOC to the destination when there is planned pile, and charging time of each pile; The third judging unit is configured to collect an updated first state in real time, obtain a second state, and determine whether the second state conforms to a second preset navigation state, wherein the second preset navigation state is a start navigation state in a guide navigation state; The second obtaining unit is configured to, if the second state conforms to the second preset navigation state, update the second periodic information by using the SOC module and the remaining time module, and obtain third periodic information, the third periodic information including remaining SOC to a next pile in navigation or remaining SOC to the destination, charging cutoff SOC of the next pile in navigation, and charging time of the next pile in navigation; The first generating unit is configured to analyze the third periodic information by using an intelligent temperature control module, and generate first prediction information, the first prediction information including battery temperature and thermal management energy consumption information of the first vehicle.

9. An electronic device, comprising: comprising a processor and a memory; The memory is configured to store; The processor is configured to execute the method of any one of claims 1 to 7 by calling.

10. A computer-readable storage medium, characterized in that, The computer program stored on the computer readable storage medium is executed by the processor to implement the steps of the method of any one of claims 1 to 7. The computer program stored on the computer readable storage medium is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

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