A method for estimating vehicle status by calling NVM values ​​stored in the cloud

Abstract

The present invention is a method for estimating the vehicle state by calling the NVM value stored in the cloud. The method is to transmit the EE data stored in the vehicle-mounted end to the server end through online storage, store it online in the form of an independent database, read and write the cloud data under the set conditions, and arbitrate whether to write it into the EE storage area through the judgment of the confidence interval. Under the condition that the internal ROM data of the vehicle is damaged due to special circumstances, the present invention can use the backup of the cloud data and the mathematical thinking of the confidence interval to evaluate the reliability, so as to re-estimate the state and prevent the previous and next state values ​​from differing too much and affecting the normal use of the vehicle. The mathematical thinking of the interval is used to evaluate the reliability, so as to re-estimate the state and prevent the previous and next state values ​​from differing too much and affecting the normal use of the vehicle.

Description

Technical Field

[0001] The present invention belongs to the technical field of cloud storage and vehicle-mounted data management, and is applicable to various vehicles, including but not limited to new energy vehicles. Background Art

[0002] With the rapid development of electrification and the Internet of Vehicles, the number of electronic devices in automotive parts has increased, and the proportion of data has increased. Therefore, important data storage technology solutions are particularly important. The vehicle status value involves the interaction between various components and affects the control strategy of the ECU. Its importance in the fields of vehicle experience and automobile safety is self-evident, so the requirements for data stability are extremely strict.

[0003] At present, traditional OEMs mainly use non-volatile memory (NVM Non-Volatile Memory) to save vehicle data. It is a memory that can save saved data even when the power is turned off. Because lithium batteries are the core power source of new energy vehicles, the importance of the battery management system (BMS) as a "nanny" is obvious. In order to monitor the battery status in real time, perform parameter estimation and fault diagnosis, historical data (such as historical faults), basic physical information (such as temperature, voltage), intermediate processing volume and output data (such as SOC, SOH) need to be stored and updated in real time. Therefore, in the battery management system, EE storage (NVM) is a very important function. It occupies ROM space and stores data that needs to be recorded (such as battery cell capacity). After receiving a call request, the data will be sent to the vehicle-mounted RAM for calculation.

[0004] In order to cope with targeted scenarios under complex working conditions and ensure the robustness of vehicle status, how to restore on-board data and effectively judge has become a research hotspot. Currently, major manufacturers mainly integrate the EE storage area on the BMS motherboard. In conventional software upgrades, in order to prevent data loss during the flashing process, the storage values ​​in the EE will not be erased. However, when the battery BCU motherboard fails and needs to be replaced, all storage values ​​inside the EE will be lost, and the vehicle status will be re-estimated for a long time, affecting customers' daily use. Therefore, an external medium is urgently needed to back up and store the data and make effective judgments on the data. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a cloud-based NVM management method, specifically a method for estimating the vehicle status by calling the cloud-based stored NVM value, and using the cloud-based stored data as a reference value to initialize the vehicle status after replacing the mainboard, so as to prevent the difference between the previous and later status values ​​from being too large and affecting the normal use of the vehicle.

[0006] The technical solution of the present invention is as follows:

[0007] A method for estimating vehicle status by calling cloud-stored NVM values, the method comprises the following steps: transmitting EE data stored on a vehicle end to a server end through online storage, storing the data online in the form of an independent database, reading and writing cloud data under set conditions, and determining whether to write the data into the EE storage area through a confidence interval.

[0008] 1. Vehicle-to-cloud interaction to upload vehicle status

[0009] The EE data stored on the vehicle side is uploaded to the cloud side, and stored online in the cloud in the form of an independent database, and an upload priority is set;.

[0010] 2. Called when restoring status value

[0011] When the vehicle-side data is lost and the status value needs to be restored, the vehicle status data stored in the cloud is called, the vehicle status initialization is started, the status value is recalculated, the confidence interval is introduced, and compared with the historical storage in the cloud.

[0012] 3. Determine effectiveness

[0013] By determining the confidence interval, it is decided whether to write into the EE storage area on the vehicle side.

[0014] 4. Update status value

[0015] If it is within the confidence interval, use the initialized result value to update the status value. If the difference is too large, use the historical Cellcap avg value.

[0016] To implement the above method, you need to first establish a cloud storage address, that is, establish a database on the cloud (server side), manage and name the database according to the vehicle model and VIN code, and set the storage path.

[0017] The present invention is based on the rapid development of communication technology and the increasingly perfect functions of the Internet of Vehicles. It can establish a separate "database" for each vehicle (VIN number). Through efficient management methods, the validity of cloud data can be arbitrated and selectively called when special circumstances occur.

[0018] The present invention adopts the cloud storage means of vehicle-cloud interaction NVM value and uses confidence interval to reasonably select cloud storage value to make the method of re-estimating the vehicle state. By adopting the above method, when encountering special circumstances causing the internal ROM data of the vehicle to be damaged, the cloud data can be backed up and the reliability can be evaluated by the mathematical thinking of confidence interval, so as to re-estimate the state and prevent the previous and next state values ​​from being too different and affecting the normal use of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0020] The present invention is further described below with reference to the accompanying drawings and embodiments:

[0021] This embodiment takes the initialization of SOH (battery health status estimation) as an example: SOH estimates the current battery cell capacity, the entire pack capacity and the battery health status, and is called as input in other functional modules. SOH has a large amount of intermediate quantities and storage in the calculation process, and needs to read and write EE storage frequently, and the historical data stored in EE has a great impact on the estimation accuracy.

[0022] See also Figure 1 ,This method includes calling the cloud storage of the vehicle data and adding the arbitration method of mathematical thinking to re-estimate the state.

[0023] 1: Create a database on the server side. Create a database on the server side. The database is managed and named according to the vehicle model and VIN code, and the storage path is set.

[0024] #Create a database (manage and name it by vehicle type and VIN code)

[0025] Create Database 001

[0026] On primary

[0027] {

[0028] name = 'BCU_EE_Cellcap_data', #Category (Battery Management System - EE Storage - Battery Cell Capacity)

[0029] filename = 'D:\BCU\BCU_EE_Cellcap_data.mdf', #Storage path setting

[0030] size=5Kb,

[0031] maxsize=50Kb#Limit the Cellcap storage value size

[0032] }

[0033] Log on

[0034] {name='BCU_EE_Cellcap_data'log,

[0035] filename='D:\BCU\BCU_EE_Cellcap_data.Idf'.

[0036] }.

[0037] 2. Storage method

[0038] Using SQL stack thinking, first-in, first-out, that is, when the storage load is full, erase the first stored data, each independent database sets up 2MB of space, to avoid resource waste, the data stored for more than one year is automatically cleared, because in most cases, the call frequency of older historical data is very low. Here is an example of an EE storage value in SOH:

[0039]

[0040] Three: Calling scene

[0041] In the event of special circumstances causing damage to the vehicle's internal ROM data, the vehicle data cloud storage will be called, mainly including the following scenarios: 1. Replacement of the main board; 2. Memory failure; 3. Tracing of historical data.

[0042] 4. Upload method

[0043] When uploading via T-BOX, you need to set the transmission enable: power-on storage, power-off storage, and fixed-cycle storage. You can use common wireless communication protocols, which require encryption and stable transmission (), and set the upload priority to prevent the loss of important data due to insufficient communication resources in special scenarios.

[0044] Five: Call initialization

[0045] For example, if the motherboard is replaced, the EE storage value is lost, and the steps for recalculating SOH are as follows:

[0046] S1: static charging, calculate the battery cell capacity Cellcap1;

[0047] S2: Repeat S1 to obtain i sets of data D = {Cellcap1, Cellcap2, ..., Cellcap i};

[0048] S3: Find the mean Cellcap result =ΣCellcap / i

[0049] Since the battery health status will not change due to the replacement of the motherboard, how to define the rationality of the recalculated value? Here we need to refer to historical data (the battery cell capacity data is transferred from the cloud) and introduce the concept of confidence interval, that is, the credibility of the measured value of the measured parameter. The calculation method is as follows:

[0050] P(c1<=μ<=c2)=1-ε

[0051] Among them, ε is the significance level (set to 0.05 here, i.e., the confidence level is 95%), c1 represents the lower confidence limit, μ represents the point estimate, and c2 represents the upper confidence limit.

[0052] Expression: Interval(c1-c2)-confidence interval.

[0053] We will recalculate the Cellcap result Compare with c1 and c2. If it is within the confidence interval, use the result value. If it is not within the confidence interval (that is, the difference is too large), use the historical Cellcap avg This avoids a large difference in the SOH calculated value before and after the motherboard is replaced, which would result in a significant reduction in available capacity, affect driving, cause customer complaints, and bring adverse effects to the product.

[0054] It can be seen from the above embodiments that the present invention mainly utilizes a cloud storage management method (which can be implemented using SQL) to transmit the EE data stored on the vehicle side to the server side through online storage, store it online in the form of an independent database, read and write cloud data under specific conditions, and arbitrate whether to write it into the EE storage area through the judgment of the confidence interval.

[0055] It should be noted that the re-estimation of the vehicle status must be achieved under networking conditions.

Claims

1. A method for estimating vehicle status by calling NVM values ​​stored in the cloud, characterized in that: The method is to transmit the EE data stored in the vehicle to the cloud, store it online in the form of an independent database, read and write the cloud data under the set conditions, and arbitrate whether to write it into the EE storage area through the determination of the confidence interval, and the steps include: (1) Vehicle-to-cloud interaction to upload vehicle status The vehicle uploads the EE data stored on the vehicle to the cloud, and stores it online in the cloud in the form of an independent database, with an upload priority setting; (2) When restoring the status value, call the vehicle status data stored in the cloud for initialization When the vehicle-side data is lost and the status value needs to be restored, the vehicle status initialization is started, the status value is recalculated, the confidence interval is introduced, and compared with the historical storage in the cloud; (3) Determine effectiveness Through the determination of the confidence interval, arbitration is conducted to determine whether to write into the EE storage area of ​​the vehicle end; (4) Update status value If it is within the confidence interval, the recalculated state value is used to update the state value; if it is not within the confidence interval, the vehicle state value historically stored in the cloud is used; For the battery health status SOH, recalculating the status value means recalculating the SOH, including S1: static charging, calculate the battery cell capacity Cellcap1; S2: Repeat S1 to obtain i sets of data D = { Cellcap1, Cellcap2, … , Cellcap i }; S3: Find its mean Cellcap result = ΣCellcap i / i; The confidence interval is calculated as follows: P(c1<=µ<=c2) = 1-ε Where ε is the significance level, c1 is the lower confidence limit, µ is the point estimate, and c2 is the upper confidence limit.

2. The method for estimating vehicle status by calling cloud-stored NVM values ​​according to claim 1, characterized in that: In the cloud, an independent database is established, which is managed and named according to the vehicle model and VIN code, and the storage path is set.

3. The method for estimating vehicle status by calling cloud-stored NVM values ​​according to claim 1 or 2, characterized in that: Situations where the status value needs to be restored include, but are not limited to, replacing the mainboard, memory failure, or tracing back historical data.

4. The method for estimating vehicle status by calling cloud-stored NVM values ​​according to claim 3, characterized in that: The cloud storage method uses SQL stack thinking, first-in-first-out, and each independent database sets up storage space. The independent database established in the cloud automatically clears data whose storage time exceeds the set time.

5. The method for estimating vehicle status by calling cloud-stored NVM values ​​according to claim 3, characterized in that: Use T-BOX to upload vehicle status and set transmission enable: power-on storage, power-off storage, and fixed-cycle storage.

6. The method for estimating vehicle status by calling cloud-stored NVM values ​​according to claim 1, characterized in that: The confidence interval determination method is: recalculate the Cellcap result Compare with c1 and c2. If it is within the confidence interval, use Cellcap result If the value is not within the confidence interval, the Cellcap value stored in the cloud history will be used. avg value.

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