Method for analyzing SOH influence factors of heavy truck battery

Abstract

The invention relates to a method for analyzing SOH influence factors of a heavy truck battery, and solves the problem that an existing method cannot accurately reflect the actual use state of a user battery. According to the method, vehicle battery data including battery rated capacity and SOH data are inspected through initial vehicle offline, data such as theoretical service life, theoretical battery cycle index and working temperature are determined in combination with a battery protocol provided by a battery manufacturer, and data such as charging and discharging, whole vehicle and battery extreme values in the vehicle operation process are integrated; and real-time detection is carried out through big data algorithm processing and analysis, so that a scientific basis is provided for maintenance and management of the battery. According to the method, the SOH influence factors of the battery can be accurately and quickly analyzed, the service life of the battery is prolonged to a certain extent, the use of battery raw materials can be reduced, and the consumption of non-renewable energy sources is reduced.

Description

Technical Field

[0001] The present invention belongs to the field of heavy trucks, and in particular relates to a method for analyzing factors affecting the SOH of a heavy truck battery. Background Art

[0002] The current method for analyzing factors affecting battery SOH (battery state of health) is generally based on accelerating battery aging through repeated charge and discharge cycles, and analyzing the influencing factors of SOH through derived characteristic factors combined with data analysis algorithms. This method has a great impact on battery life, and the experimental conditions are quite different from the actual user environment, and cannot accurately reflect the actual usage status of the user's battery. Summary of the invention

[0003] The present invention aims to provide a system and method for analyzing the SOH of heavy truck batteries, and to reduce the SOH decline rate by providing improvement suggestions based on the analysis results. The method inspects the vehicle battery data at the initial vehicle offline, including the battery rated capacity and SOH data, and determines the theoretical service life, theoretical battery cycle number, operating temperature and other data in combination with the battery protocol provided by the battery manufacturer, integrates the data of charging and discharging during vehicle operation, the whole vehicle, and the battery extreme value, and then performs real-time detection through big data algorithm processing and analysis, providing a scientific basis for battery maintenance and management.

[0004] The present invention is achieved by the following technical solutions:

[0005] A method for analyzing factors affecting the SOH of a heavy truck battery, comprising the following steps:

[0006] S1: Battery data collection:

[0007] After the vehicle is offline, the battery rated capacity, SOH, and theoretical cycle times are recorded;

[0008] S2: Battery alarm calculation:

[0009] 1) SOH alarm: By collecting the battery data reported by the vehicle and combining the SOH calculation algorithm to calculate the battery SOH in real time, an alarm is issued when the vehicle battery SOH is less than or equal to 90%. The battery SOH calculation formula is as follows:

[0010]

[0011] Among them, SOC1 is the charging start SOC, SOC2 is the charging end SOC, C0 is the battery rated capacity, and C1 is the charging capacity;

[0012] 2) Temperature alarm: monitor battery temperature data, and issue a battery temperature alarm when the temperature is greater than or equal to 65°C or less than or equal to -10°C;

[0013] 3) Charge and discharge speed alarm: Identify the vehicle charging status, use the charging speed formula to calculate the charging speed during charging, and issue a charging speed alarm when the charging speed is greater than or equal to 1C; identify the vehicle running status, use the discharge speed formula to calculate the discharge speed during discharge, and issue a discharge speed alarm when the discharge speed is greater than or equal to 1C;

[0014] Charging speed C = charging current (A) / battery rated capacity (Ah)

[0015] Discharge rate C = discharge current (A) / battery rated capacity (Ah)

[0016] 4) Discharge depth: monitor the battery charging starting SOC, calculate the discharge depth DOD using the discharge depth formula, and issue a discharge depth alarm when the discharge depth is less than or equal to 10%;

[0017] DOD = (1-remaining power / total power)*100%

[0018] S3: Analysis of SOH:

[0019] The weight ratio of temperature, charging speed, discharge depth, and discharge speed affecting SOH is calculated by standardization method;

[0020] 1) Preliminary assessment of the importance of existing vehicle battery temperature alarm, deep discharge alarm, discharge speed alarm, and charging speed alarm data;

[0021] 2) Calculate the sum of weights

[0022] Total weight = the sum of the importance of high temperature, low temperature, depth of discharge, charging speed and discharge speed;

[0023] 3) Standardized weight calculation

[0024] Divide the importance of each by the sum of weights to get their respective standardized weights;

[0025] S4: Based on the alarm data generated in step (2), including the number of high temperature alarms, the number of low temperature alarms, the number of deep discharges, the number of charge speed alarms, and the number of discharge speed alarms, analyze the impact of each on SOH:

[0026] Specifically: Impact value = number of alarms × standardized weight

[0027] According to the impact value, the main factors affecting SOH are analyzed and corresponding suggestions are given.

[0028] In S3, the high temperature alarm importance is set to 9, the deep discharge importance is set to 7, the discharge speed importance is set to 6, the charging speed importance is set to 4, and the low temperature alarm importance is set to 3.

[0029] The present invention can accurately and quickly analyze the factors affecting battery SOH, extend the battery life to a certain extent, reduce the use of battery raw materials, and reduce the consumption of non-renewable energy. DETAILED DESCRIPTION

[0030] The present invention realizes intelligent calculation, identification, early warning and prediction of SOH of heavy truck batteries based on battery data during vehicle operation and vehicle data combined with a big data algorithm model. Specifically, the method consists of the following steps: (1) Battery data collection: After the vehicle is offline, the battery rated capacity, SOH and theoretical cycle number are recorded.

[0031] (2) Battery alarm calculation:

[0032] 1) SOH alarm: By collecting the battery data reported by the vehicle and combining the SOH calculation algorithm to calculate the battery SOH in real time, an alarm is issued when the vehicle battery SOH is less than or equal to 90%. The battery SOH calculation formula is as follows:

[0033]

[0034] Among them, SOC1 is the starting SOC of charging, SOC2 is the ending SOC of charging, C0 is the rated capacity of the battery, and C1 is the charging capacity.

[0035] 2) Temperature alarm: monitor battery temperature data, when the temperature is greater than or equal to 65℃ or less than or equal to -10℃

[0036] When (supports dynamic adjustment), the battery temperature alarm is issued;

[0037] 3) Charge and discharge speed alarm: Identify the vehicle charging status, use the charging speed formula to calculate the charging speed during charging, and issue a charging speed alarm when the charging speed is greater than or equal to 1C; identify the vehicle running status, use the discharge speed formula to calculate the discharge speed during discharge, and issue a discharge speed alarm when the discharge speed is greater than or equal to 1C;

[0038] Charging speed C = charging current (A) / battery rated capacity (Ah)

[0039] Discharge rate C = discharge current (A) / battery rated capacity (Ah)

[0040] 4) Discharge depth: monitor the battery charging starting SOC, calculate the discharge depth (DOD) using the discharge depth formula, and issue a discharge depth alarm when the discharge depth is less than or equal to 10%;

[0041] DOD = (1-remaining power / total power)*100%

[0042] (3) Analysis of SOH

[0043] The influence of temperature, charging speed, discharge depth and discharge speed on SOH weight ratio is calculated through standardization method.

[0044] 1) Preliminary assessment through existing vehicle battery temperature alarm, deep discharge alarm, discharge speed alarm, and charging speed alarm data:

[0045] High temperature alarm: severity level is 9 (maximum is 10)

[0046] Deep discharge: severity level 7

[0047] Discharge rate: importance level 6

[0048] Charging speed: importance level 4

[0049] Low temperature alarm: severity level 3

[0050] 2) Calculate the sum of weights

[0051] Total weight = high temperature + low temperature + depth of discharge + charging speed + discharge speed = 29

[0052] 3) Standardized weight calculation

[0053] Normalized weight for high temperature = 9 / 29 = 0.31

[0054] Normalized weight for deep discharge = 7 / 29 = 0.241

[0055] Normalized weight of discharge rate = 6 / 29 = 0.206

[0056] Normalized weight of charging speed = 4 / 29 = 0.138

[0057] Normalized weight for low temperature = 3 / 29 = 0.103

[0058] (4) Based on the alarm data generated in step (2), including the number of high temperature alarms, the number of low temperature alarms, the number of deep discharges, the number of charge speed alarms, and the number of discharge speed alarms, analyze the main factors affecting SOH. The alarm data example and analysis process are as follows:

[0059]

[0060] Calculate the impact value of each attribute:

[0061] 1) High temperature: 28*0.31=8.68

[0062] 2) Deep discharge: 56*0.241=13.496

[0063] 3) Discharge rate: 31*0.206=6.386

[0064] 4) Charging speed: 72*0.138=9.936

[0065] 5) Low temperature: 31*0.103=3.193

[0066] Based on the above results, it can be inferred that the factors affecting the battery SOH are deep discharge, charging speed, and high temperature. Users are advised to avoid frequent deep discharge, replace chargers, and pay attention to high temperature environments.

[0067] The advantages of the present invention are that the terminal sensor reports the vehicle battery data, the alarm data is generated in combination with the setting of the alarm thresholds of various battery parameters, the weight ratio of each alarm item is calculated by the standardization method, and then the main factors affecting the battery SOH are analyzed.

[0068] The present invention analyzes the factors affecting battery SOH based on the initial data when the vehicle is offline and the data during operation, which is more in line with the actual scenario of users.

Claims

1. A method for analyzing the factors affecting the SOH of heavy truck batteries, characterized by: The following steps are involved: S1: Battery data collection: After the vehicle is offline, the battery rated capacity, SOH, and theoretical cycle times are recorded; S2: Battery alarm calculation: 1) SOH alarm: By collecting the battery data reported by the vehicle and combining the SOH calculation algorithm to calculate the battery SOH in real time, an alarm is issued when the vehicle battery SOH is less than or equal to 90%. The battery SOH calculation formula is as follows: Among them, SOC1 is the charging start SOC, SOC2 is the charging end SOC, C0 is the battery rated capacity, and C1 is the charging capacity; 2) Temperature alarm: monitor battery temperature data. When the temperature is greater than or equal to 65°C or less than or equal to -10°C, a battery temperature alarm is issued; 3) Charge and discharge speed alarm: Identify the vehicle charging status, use the charging speed formula to calculate the charging speed during charging, and issue a charging speed alarm when the charging speed is greater than or equal to 1C; identify the vehicle running status, use the discharge speed formula to calculate the discharge speed during discharge, and issue a discharge speed alarm when the discharge speed is greater than or equal to 1C; Charging speed C = charging current (A) / battery rated capacity (Ah) Discharge rate C = discharge current (A) / battery rated capacity (Ah) 4) Discharge depth: monitor the battery charging starting SOC, calculate the discharge depth DOD using the discharge depth formula, and issue a discharge depth alarm when the discharge depth is less than or equal to 10%; DOD = (1-remaining power / total power)*100% S3: Analysis of SOH: The weight ratio of temperature, charging speed, discharge depth, and discharge speed affecting SOH is calculated by standardization method; 1) Preliminary assessment of the importance of existing vehicle battery temperature alarm, deep discharge alarm, discharge speed alarm, and charging speed alarm data; 2) Calculate the sum of weights Total weight = the sum of the importance of high temperature, low temperature, depth of discharge, charging speed and discharge speed; 3) Standardized weight calculation Divide the importance of each by the sum of weights to get their respective standardized weights; S4: Based on the alarm data generated in step S2, including the number of high temperature alarms, the number of low temperature alarms, the number of deep discharges, the number of charge speed alarms, and the number of discharge speed alarms, analyze the impact values ​​of each on SOH, specifically: Impact value = number of alarms × standardized weight According to the impact value, the main factors affecting SOH are analyzed and corresponding suggestions are given.

2. According to claim 1, a method for analyzing the influencing factors of SOH of heavy truck batteries is characterized in that: in S3, the high temperature alarm importance is set to 9, the deep discharge importance is set to 7, the discharge speed importance is set to 6, the charging speed importance is set to 4, and the low temperature alarm importance is set to 3.

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