Intelligent battery management system platform and detection method

Abstract

The invention belongs to the field of new energy automobile practical training, and particularly relates to a battery intelligent management system platform and a detection method, and the platform comprises a sensor module which is used for collecting current, voltage and temperature data of a battery; the microcontroller unit (MCU) is used for processing and analyzing the data acquired by the sensor and making a control decision; the communication module is used for realizing wireless data transmission with external equipment; and the storage module is used for storing historical data of the battery. The sensor module comprises a high-precision Hall current sensor which is used for measuring charging and discharging current of a battery in real time; the system can analyze and mine a large amount of battery data, and provides valuable reference for research, development, production and maintenance of batteries. And meanwhile, the user can interact with the system in various modes, so that the required information can be conveniently and quickly obtained.

Description

Technical Field

[0001] The present invention relates to the field of new energy vehicle training, and in particular to a battery intelligent management system platform and a detection method. Background Art

[0002] With the rapid development of electronic devices and electric vehicles, the performance and safety of batteries as key components of energy storage have become crucial. However, existing battery management systems have many deficiencies in accuracy, reliability and intelligence. For example, traditional battery management systems are difficult to monitor various parameters of the battery in real time and accurately, and are unable to detect potential faults and safety hazards in a timely manner; the accuracy of battery status assessment and remaining power estimation is low, which affects the efficiency and endurance of the equipment; at the same time, the battery charging and discharging control strategy is not optimized enough, which may shorten the battery life. Therefore, it is of great practical significance to develop a more advanced, intelligent and reliable battery intelligent management system platform and detection method. Summary of the invention

[0003] The purpose of the present invention is to provide an advanced battery intelligent management system platform and detection method to solve the problems raised in the above background technology.

[0004] The technical solution adopted by the present invention is: an advanced battery intelligent management system platform and detection method, including the following parts:

[0005] 1. Hardware Architecture

[0006] Sensor Module

[0007] Current sensor: used to measure the battery charging and discharging current in real time. It uses a high-precision Hall current sensor that can accurately detect tiny current changes.

[0008] Voltage sensor: measures the voltage of the battery cell, using a voltage divider resistor network combined with a high-precision ADC chip to ensure the accuracy of voltage measurement.

[0009] Temperature sensor: monitors the temperature inside and outside the battery, using thermistor or thermocouple sensors installed at key locations of the battery.

[0010] Microcontroller Unit (MCU)

[0011] A high-performance 32-bit microcontroller with powerful computing capabilities and rich peripheral interfaces is selected to be responsible for data acquisition, processing and control decision-making.

[0012] Communication Module

[0013] Bluetooth module: used for short-range wireless communication with mobile devices, allowing users to check battery status in real time.

[0014] Wi-Fi module: enables remote data transmission with cloud servers, facilitating big data analysis and remote monitoring.

[0015] Storage Module

[0016] Non-volatile memory: used to store historical battery data, such as charge and discharge times, operating temperature curve, etc., for fault diagnosis and performance analysis.

[0017] 2. Software System

[0018] Data collection and preprocessing

[0019] The sensor data is collected at a fixed sampling frequency, and filtered and denoised to remove interference signals and improve data accuracy.

[0020] Battery status estimation

[0021] The Kalman filter algorithm is combined with the battery equivalent model to estimate the battery state of charge (SOC) and state of health (SOH) in real time.

[0022] Establish an accurate battery equivalent model, consider factors such as the battery's internal resistance and polarization effect, and improve the accuracy of state estimation.

[0023] Fault diagnosis and early warning

[0024] Based on the collected data and preset thresholds, intelligent algorithms are used to diagnose battery faults such as overcharging, over-discharging, and overheating in real time.

[0025] Once a fault is detected, an audible and visual alarm signal is immediately issued, and early warning information is sent to the user and the monitoring center through the communication module.

[0026] Charge and discharge control strategy

[0027] According to the battery status and user needs, the charging and discharging current and voltage are intelligently optimized to extend the battery life.

[0028] Pulse charging technology and trickle charging mode are adopted to improve charging efficiency and safety.

[0029] User Interface and Interaction

[0030] Develop mobile applications and web interfaces to facilitate users to intuitively view the real-time status, historical data and fault information of the battery.

[0031] Supports users to set personalized battery management parameters and reminder functions.

[0032] 3. Detection Method

[0033] Static detection

[0034] When the battery is at rest, measure the open circuit voltage and internal resistance of the battery to evaluate the initial performance and health of the battery.

[0035] Dynamic Detection

[0036] During the battery charging and discharging process, the changes in current, voltage, temperature and other parameters are monitored in real time to analyze the dynamic characteristics of the battery.

[0037] Use step current or pulse discharge methods to detect the battery's response capability and internal resistance changes.

[0038] Capacity detection

[0039] Through complete charge and discharge cycles, the actual capacity of the battery is accurately measured, compared with the nominal capacity, and the degree of battery attenuation is evaluated.

[0040] Consistency detection

[0041] For battery packs composed of multiple cells, the consistency of parameters such as voltage and capacity between each single cell is tested to promptly identify batteries with large performance differences.

[0042] 4. System Advantages

[0043] High-precision state estimation

[0044] Through advanced algorithms and precise models, the estimation error of battery SOC and SOH can be controlled within 5%, providing users with accurate information on remaining battery power and health status.

[0045] Real-time fault diagnosis and early warning

[0046] It can detect battery failures within milliseconds and issue warnings in a timely manner, effectively avoiding the occurrence of battery safety accidents.

[0047] Optimized charge and discharge control strategy

[0048] Compared with traditional charging and discharging methods, it can extend battery life by more than 20% and reduce user costs.

[0049] Powerful data analysis and interactive functions

[0050] The system can analyze and mine a large amount of battery data, providing valuable reference for battery research and development, production and maintenance. At the same time, users can interact with the system in a variety of ways to obtain the required information conveniently and quickly. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a system principle diagram of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Embodiment 1

[0054] Taking the electric vehicle battery management system as an example, the system platform is installed in the battery pack of the electric vehicle. The sensor module collects the battery current, voltage and temperature data in real time and transmits it to the MCU. The MCU processes and analyzes the data, estimates the battery SOC and SOH, and intelligently controls the output current and voltage of the charger according to the vehicle's driving status and the user's charging needs. At the same time, the battery data is uploaded to the cloud server through the Wi-Fi module, and the vehicle manufacturer and operation and maintenance personnel can view the operation of the vehicle battery through the web page for remote monitoring and fault diagnosis.

[0055] Embodiment 2

[0056] In energy storage power stations, the battery intelligent management system platform of the present invention can centrally manage a large number of battery packs. The parameters of each battery cell are collected through sensors distributed in the battery pack, and the data is aggregated to the central controller through the communication network. The central controller analyzes and processes the data to achieve balanced charging, fault warning and capacity management of the battery pack. Operation and maintenance personnel can check the status of the battery pack at any time through the mobile application and perform maintenance and replacement work in a timely manner.

[0057] Embodiment 3

[0058] For portable electronic devices, such as smartphones and tablets, this system can be integrated into the device. During the charging and use of the device, the battery status is monitored in real time, the charging strategy is optimized, overcharging and over-discharging are prevented, and the battery life is extended. Users can view detailed information about the battery through the device's built-in application and use it reasonably according to the prompts.

[0059] Experimental results and analysis:

[0060] In order to verify the effectiveness of the battery intelligent management system platform and detection method of the present invention, the following experiments were conducted:

[0061] State estimation accuracy experiment:

[0062] Batteries of different types and capacities were selected for charge and discharge experiments, and the SOC and SOH of the batteries were estimated using the system of the present invention and the traditional method. The experimental results show that the SOC estimation error of the system of the present invention is less than 3%, and the SOH estimation error is less than 5%, while the estimation errors of the traditional method are about 8% and 10%, respectively.

[0063] Fault diagnosis experiment:

[0064] The fault conditions of battery overcharge, over discharge, overheating, etc. were simulated to observe the diagnostic response time and accuracy of the system of the present invention. The experimental results show that the system can accurately diagnose the fault within 100 milliseconds and send out an early warning signal, effectively avoiding further deterioration of the fault.

[0065] Charge and discharge control strategy experiment:

[0066] The effects of the optimized charge and discharge control strategy of the present invention and the traditional charge and discharge method on the battery life are compared. After multiple cycle charge and discharge experiments, the battery life of the strategy of the present invention is extended by about 25%, while the battery life of the traditional method is relatively short.

[0067] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. An advanced battery intelligent management system platform, It is characterized in that include: Sensor module, used to collect battery current, voltage and temperature data; Microcontroller unit (MCU), which is used to process and analyze the data collected by sensors and make control decisions; Communication module, used to realize wireless data transmission with external devices; The storage module is used to store the historical data of the battery.

2. The battery intelligent management system platform according to claim 1, It is characterized in that The sensor module includes: a high-precision Hall current sensor for measuring the charge and discharge current of the battery in real time; A voltage sensor using a voltage divider resistor network combined with a high-precision ADC chip is used to measure the voltage of a battery cell; Thermistor or thermocouple sensors to monitor the temperature inside and outside the battery.

3. The battery intelligent management system platform according to claim 1, It is characterized in that The microcontroller unit uses a high-performance 32-bit microcontroller with powerful computing capabilities and rich peripheral interfaces.

4. The battery intelligent management system platform according to claim 1, It is characterized in that The communication module includes a Bluetooth module and a Wi-Fi module, which are respectively used for short-range wireless communication with a mobile device and for remote data transmission with a cloud server.

5. The battery intelligent management system platform according to claim 1, It is characterized in that The storage module adopts a non-volatile memory for storing historical data such as the number of charge and discharge times and the operating temperature curve of the battery.

6. A detection method for an advanced battery intelligent management system platform, It is characterized in that The following steps are involved: Static testing: When the battery is at rest, the open circuit voltage and internal resistance of the battery are measured to evaluate the initial performance and health of the battery. Dynamic detection: During the battery charging and discharging process, the changes in current, voltage, temperature and other parameters are monitored in real time to analyze the dynamic characteristics of the battery; Capacity detection: through complete charge and discharge cycles, the actual capacity of the battery is accurately measured, compared with the nominal capacity, and the degree of battery attenuation is evaluated; Consistency testing: For battery packs composed of multiple cells, the consistency of parameters such as voltage and capacity between each single cell is tested to promptly identify batteries with large performance differences.

7. The detection method according to claim 6, It is characterized in that In the dynamic detection, a step current or pulse discharge method is used to detect the response capability and internal resistance change of the battery.

8. The detection method according to claim 6, It is characterized in that The software system of the battery intelligent management system platform includes: Data acquisition and preprocessing: collecting sensor data at a fixed sampling frequency and performing filtering and denoising; Battery state estimation, using the Kalman filter algorithm combined with the battery equivalent model to estimate the battery's state of charge (SOC) and state of health (SOH) in real time; Fault diagnosis and early warning: Based on the collected data and preset thresholds, intelligent algorithms are used to diagnose battery overcharge, over-discharge, overheating and other faults in real time, and issue early warnings in a timely manner; Charge and discharge control strategy, intelligently optimizes charge and discharge current and voltage according to battery status and user needs; User interface and interaction: develop mobile applications and web interfaces to facilitate users to intuitively view the real-time status, historical data and fault information of the battery, and support users to set personalized battery management parameters and reminder functions.

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