Wide-voltage self-adaptive multi-mode programmable charging and detecting all-in-one machine
By designing a wide-voltage adaptive multi-mode programmable charging and testing integrated machine, the problems of single function and poor environmental adaptability of charging equipment have been solved, realizing high-precision battery status assessment and multi-device management, and improving the intelligence and safety of the equipment.
Patent Information
- Application Number
- CN202511987891.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-26
- Publication Date
- 2026-02-17
AI Technical Summary
Existing charging equipment has limited functionality, cannot accurately assess battery status, cannot independently assess battery voltage and capacity in the absence of communication connection or under static conditions, has poor environmental adaptability, is not compatible with multiple devices, and suffers from problems such as micro-discharge of batteries and low charging efficiency at low temperatures.
Design a wide-voltage adaptive multi-mode programmable charging and testing all-in-one machine, including a main control MCU, a wide-voltage input AC-DC conversion module, a programmable power output module, a battery status detection module, a temperature sensing module, a wireless communication module, and a load relay. It can achieve independent evaluation and communication collaboration, support multi-device management, and has wide voltage input and all-weather adaptability.
It achieves high-precision battery status assessment, supports multi-device management, improves the intelligence and environmental adaptability of equipment, reduces user procurement costs, and improves operation and maintenance efficiency and safety.
Smart Images
Figure CN121546781A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of charging and testing integrated machines, in particular to a wide-voltage self-adaptive multi-mode programmable charging and testing integrated machine. BACKGROUND
[0002] With the development of electric vehicles, energy storage systems and portable devices, batteries are widely used due to their high energy density and long cycle life. The supporting charging equipment technology is also constantly innovating. Traditional chargers have single function, usually only have basic constant current and constant voltage charging modes, and are difficult to meet the charging needs of batteries in complex application scenarios. Users lack the acquisition of battery information, including the timely acquisition of battery health, battery remaining capacity and other content. At present, the development of this technical field mainly reflects in multi-mode selection, interaction with the battery management system and preliminary fault diagnosis, etc. In related key technologies, the current technical level has the following characteristics and limitations: Battery state evaluation: Most charging equipment can only complete the basic charging function and cannot effectively evaluate the state of charge and health of the battery. Although a few high-end devices can obtain data through communication with the battery management system, they lack the ability to independently evaluate the battery voltage and capacity without communication connection or in static conditions, or are connected to other devices at the same time, such as external display devices, and cannot achieve the effect of monitoring where the person is. Function integration and intelligence: The market existing products are mostly single-function chargers or testers, and few devices integrate charging and deep detection functions. The detection function of these devices is often limited to simple judgment of basic parameters such as voltage and current, and cannot cooperate with BMS data. In addition, some high-end chargers carry wireless communication functions, but the connection is single and cannot simultaneously compatible with multiple device management. General-purpose devices with software programmable output are still scarce, and users often need to equip different batteries with special chargers, which has poor flexibility. In addition, the circuit power consumption during standby may cause the battery to continuously discharge a small amount, and long-term connection will damage the battery health. The existing design lacks attention to this problem, and the environmental adaptability is insufficient. Conventional chargers have low charging efficiency and safety hazards in low-temperature environments. The existing solutions mostly use external heating sheets to preheat the battery pack, and then start charging when the temperature rises to the appropriate range. Wide-voltage input self-adaptive capability: Many charging equipment, especially high-power chargers, usually have a narrow range of AC input voltage, which is difficult to adapt to scenarios with severe grid fluctuations or the need to use different standard power sources. Although there are some power supply designs that support wide-voltage input, they often focus on implementing basic voltage conversion functions and fail to form intelligent linkage with subsequent charging strategies and battery detection functions. Their conversion efficiency is usually not optimal across the entire voltage range, especially at the upper and lower limits of voltage, where the efficiency may be significantly reduced. Therefore, it is necessary to design a wide-voltage adaptive multi-mode programmable charging and testing integrated machine to solve the above problems, and realize a comprehensive technical scheme of wide-voltage adaptation, high-precision autonomous evaluation, intelligent charging and testing integration, and multi-device parallel management. SUMMARY
[0003] The purpose of the present application is to provide a wide-voltage adaptive multi-mode programmable charging and testing integrated machine to solve the problems raised in the background art.
[0004] To achieve the above purpose, the present application provides the following technical scheme: a wide-voltage adaptive multi-mode programmable charging and testing integrated machine, comprising a master control unit (MCU), a wide-voltage input AC-DC conversion module, a programmable power output module, a battery state detection module, a temperature sensing module, a wireless communication module, and a load relay. The wide-voltage input AC-DC conversion module is used to convert an AC input voltage of 85V-265V into a DC bus voltage. The programmable power output module is used to adjust the output voltage and current according to the instructions of the master control unit (MCU). The battery state detection module is connected to the master control unit (MCU) and is used to collect battery voltage and current signals. The temperature sensing module includes a thermocouple arranged at the charging cable connector and an NTC thermistor arranged at the device housing, and is used to receive and compare battery internal temperature data from the BMS. The wireless communication module is a low-power Bluetooth (BLE) based communication module, which is used to interact with external BMS and mobile phone APP. The load relay is connected between the charging and testing integrated machine and the battery and is controlled by the master control unit (MCU). The charging and testing integrated machine includes an independent working mode and a BMS communication cooperative mode. In the independent working mode, the master control unit (MCU) is configured to: Control the load relay to be disconnected, so that the battery is in a resting state, and sample the open-circuit voltage (OCV) of the resting battery through the high-precision ADC in the battery state detection module. According to the sampled OCV value, query the OCV-SOC comparison table for different battery types pre-stored in the memory to obtain an initial SOC estimation value. During the subsequent charging process, the initial SOC estimation value is corrected through closed-loop feedback by integrating the charging current with respect to time to calculate the charging capacity. In the pre-charge phase, the dynamic internal resistance of the battery is calculated by rapidly adjusting the voltage and current and using high-speed acquisition of the current-voltage response curve, the formula is: DCR=ΔV / ΔI, and the current DCR value is compared with the pre-stored nominal internal resistance of the battery in the new state, and the battery health state evaluation value is obtained; In the BMS communication cooperative mode, the master MCU is further configured to: Connect with the BMS through the wireless communication module and obtain battery data, which is used for autonomous learning and correction of the OCV-SOC comparison table.
[0005] Preferably, the master MCU is further configured to query the pre-stored temperature and current characteristic matrix according to the multi-source temperature data collected by the temperature sensing module, dynamically adjust the charging current, and realize the battery self-preheating function in low temperature environment and the current limiting protection function in high temperature environment.
[0006] Preferably, the master MCU is further configured to execute a repair pulse charging mode to generate pulse output with specific voltage, current, frequency and duty cycle for battery depolarization repair.
[0007] Preferably, the master MCU is further configured to judge the battery health degree according to the SOH evaluation value, and if the SOH evaluation value is lower than the pre-set safety threshold, stop the charging process and issue an alarm.
[0008] Preferably, the wireless communication module uses a multi-mode Bluetooth SOC chip supporting multi-connection characteristics, and the memory of the charging and detection integrated machine pre-stores characteristic identification codes of multiple BMS brands and their corresponding communication instruction sets, and the master MCU is configured to scan and analyze the characteristic identification codes in the BMS broadcast packet through the wireless communication module, match the analyzed characteristic identification codes with the local stored protocol library, and if the matching is successful, automatically call the corresponding communication instruction set to establish GATT connection with the target BMS and perform data interaction.
[0009] Preferably, the master MCU is configured to simultaneously maintain GATT connection with multiple BMS, and through the multiplexing mechanism of the software stack, data exchange is performed with each connected BMS in the time slice polling or event triggering mode.
[0010] Preferably, the charging and detection integrated machine supports online updating and expanding of the pre-stored BMS communication protocol library in its memory through external devices.
[0011] Preferably, the master MCU is configured to receive and analyze heterogeneous data from multiple connected BMS, format and aggregate the analyzed data, and upload the aggregated data packet to the mobile phone APP through a single Bluetooth connection.
[0012] Preferably, the wide voltage input AC-DC conversion module comprises an active power factor correction circuit and an LLC resonant converter.
[0013] Preferably, the programmable power output module adopts a phase-shift full-bridge topology structure, and the main control MCU converts an adjustable PWM signal into an analog direct current voltage through an RC low-pass filter circuit to adjust the duty cycle of the power switch tube, so as to dynamically set the output voltage and current value.
[0014] Compared with the prior art, the wide voltage adaptive multi-mode programmable charging and testing integrated machine has the following beneficial effects: 1. The wide voltage adaptive multi-mode programmable charging and testing integrated machine greatly improves the evaluation accuracy, adopts a communication-independent evaluation and communication self-learning correction double-engine mode, and through OCV and ampere-hour integral fusion algorithm and parameter learning, the SOC estimation error can be controlled within a small range, the evaluation of the battery health state is also more objective, and the limitation of the traditional device that is seriously dependent on a single data source or completely dependent on BMS communication is completely changed. In any scenario, high-precision and high-reliability battery state data can be obtained. 2. The wide voltage adaptive multi-mode programmable charging and testing integrated machine has a dynamic protocol library and a Bluetooth online updating mechanism, so that a single device can adapt to many BMS brands, realizes universality, greatly reduces the cost of purchasing multiple special-purpose devices for users, and enables a single person to complete centralized monitoring and maintenance of a large number of battery packs on a mobile phone, thereby improving the operation and maintenance efficiency by several times and overcoming the disadvantage that BMS information cannot be obtained when communication is unavailable.
[0015] 3. The wide voltage adaptive multi-mode programmable charging and testing integrated machine is self-adaptive to environmental current, uses a K-type thermocouple or an NTC thermistor as a temperature sensor, is directly embedded in the power cable inside the output terminal of the charging device, can directly contact the battery pole or the shell, realizes accurate measurement of the core temperature, avoids environmental temperature interference, fundamentally improves safety, upgrades from traditional monitoring voltage to voltage, current and temperature three-parameter closed-loop cooperative control, actively prevents thermal runaway risk, and has full-weather adaptability. A set of scheme can cope with severe cold and scorching heat without user intervention, the device automatically makes the optimal decision, and the reliability and user experience of the product are greatly improved. BRIEF DESCRIPTION OF DRAWINGS
[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description only constitute some of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor. Fig. 1 The independent working flowchart of the charging and detecting all-in-one machine; Fig. 2 The multi-protocol BMS communication and parallel connection management flowchart. DETAILED DESCRIPTION
[0017] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.
[0018] In the present application, unless otherwise explicitly specified and limited, the terms such as "mounting", "connection", "linking", "fixing" and the like should be understood in a broad sense, for example, can be fixed connection, or detachable connection, or integrated; can be mechanical connection, or electrical connection; can be directly connected, or indirectly connected through an intermediate medium; can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances. Embodiment one
[0019] Please refer to Figs. 1-2 The present application provides a technical solution: a wide-voltage adaptive multi-mode programmable charging and detecting all-in-one machine, comprising a master control MCU, a wide-voltage input AC-DC conversion module, a programmable power output module, a battery state detection module, a temperature sensing module, a wireless communication module and a load relay. The wide-voltage input AC-DC conversion module is used to convert the 85V-265V AC input voltage into a DC bus voltage. The programmable power output module is used to adjust the output voltage and current according to the instructions of the master control MCU. The battery state detection module is connected to the master control MCU, and is used to collect the battery voltage and current signals. The temperature sensing module comprises a thermocouple arranged at the charging cable connector and an NTC thermistor arranged at the device shell, and is used to receive and compare the internal battery temperature data from the BMS. The wireless communication module is a Bluetooth Low Energy (BLE) based communication module for data interaction with external BMS and mobile phone APP. The load relay is connected between the charging and detecting integrated machine and the battery and is controlled by the master MCU. The charging and detecting integrated machine includes an independent working mode and a BMS communication cooperative mode. In the independent working mode, the master MCU is configured to: control the load relay to be disconnected, so that the battery is in a resting state, and sample the open-circuit voltage of the battery after resting by a high-precision ADC in the battery state detection module; query an OCV-SOC comparison table for different battery types pre-stored in a memory according to the sampled OCV value, and obtain an initial SOC estimation value; In a subsequent charging process, the initial SOC estimation value is corrected through closed-loop feedback in combination with the integral calculation of charging current with respect to time; In the pre-charging phase, the dynamic internal resistance of the battery is calculated by rapidly adjusting the voltage and current and using a high-speed current-voltage response curve, the formula is DCR=ΔV / ΔI, and the current DCR value is compared with and normalized with the nominal internal resistance of the battery in a new state, to obtain a battery health state evaluation value; In the BMS communication cooperative mode, the master MCU is further configured to: connect with the BMS through the wireless communication module and obtain battery data, for autonomous learning and correction of the OCV-SOC comparison table.
[0020] The master MCU is further configured to query a pre-stored temperature and current characteristic matrix according to multi-source temperature data collected by the temperature sensing module, dynamically adjust the charging current, and realize the battery self-preheating function in a low-temperature environment and the current limiting protection function in a high-temperature environment.
[0021] The master MCU is further configured to execute a repair pulse charging mode to generate pulse output with specific voltage, current, frequency and duty cycle for battery depolarization repair.
[0022] The master MCU is further configured to judge the battery health degree according to the SOH evaluation value, and if the SOH evaluation value is lower than a preset safety threshold, stop the charging process and issue an alarm.
[0023] The wireless communication module adopts a multi-mode Bluetooth SOC chip supporting a multi-connection feature, a plurality of characteristic identification codes of BMS brands and corresponding communication instruction sets are pre-stored in a memory of the charging and detecting integrated machine, and the master control MCU is configured to scan and analyze the characteristic identification codes in the surrounding BMS broadcast packets through the wireless communication module, match the analyzed characteristic identification codes with the locally stored protocol library, and if the matching is successful, automatically call the corresponding communication instruction set to establish a GATT connection with the target BMS and perform data interaction.
[0024] The master control MCU is configured to simultaneously maintain GATT connections with a plurality of BMSs, and through a multiplexing mechanism of a software stack, perform data exchange with each connected BMS in a time slice polling or event triggering manner.
[0025] The charging and detecting integrated machine supports online updating and expansion of the pre-stored BMS communication protocol library in the memory through an external device.
[0026] The master control MCU is configured to receive and analyze heterogeneous data from a plurality of connected BMSs, format and aggregate the analyzed data, and upload the aggregated data packets to a mobile phone APP through a single Bluetooth connection.
[0027] The wide-voltage-input AC-DC conversion module includes an active power factor correction circuit and an LLC resonant converter.
[0028] The programmable power output module adopts a phase-shifted full-bridge topology structure, the master control MCU outputs a modulatable PWM signal, which is converted into an analog DC voltage through an RC low-pass filter circuit, to adjust the duty cycle of the power switch tube, thereby dynamically setting the output voltage and current values.
[0029] In actual operation, when the device is in use, 1. Working principle of high-precision battery state evaluation: Independent evaluation mode: When the device cannot communicate with the battery management system, this mode is started; SOC estimation: the master control MCU first controls the load relay to be disconnected, so that the battery load is completely disconnected and enters a resting state. After a preset time, the high-precision ADC module samples the open-circuit voltage of the battery, and the MCU compares the sampled OCV value with the OCV-SOC comparison table pre-stored in the memory for different battery types to obtain an initial SOC estimation value. During the subsequent charging process, the MCU calculates the cumulative charging capacity in real time by integrating the charging current and time, and continuously corrects the initial OCV estimation value through closed-loop feedback, gradually approaching the true SOC of the battery; SOH evaluation: During the pre-charge phase, when the charging current is stable, the system collects the current and voltage response data of the battery at a high speed. By calculating the ratio of the voltage change and the current change, the current dynamic internal resistance (DCR) of the battery is obtained. The MCU normalizes this DCR value with the nominal internal resistance of the battery in the new state in the database, and thus quantitatively evaluates the health status of the battery, i.e., the capacity attenuation percentage. Communication coordination and learning mode: When the device can establish communication with the BMS, the host MCU obtains the accurate battery data provided by the BMS through the wireless communication module. The system uses these data to cross-verify, correct and autonomously learn the internally pre-stored OCV-SOC reference table and internal resistance parameters, so that the subsequent independent evaluation algorithm parameters are continuously optimized, and the evaluation accuracy is continuously improved. 2. Working principle of multi-mode adaptive intelligent charging: The charging process is dynamically controlled by the host MCU based on multi-source information: Environmental perception: The system collects temperature data from three key parts in real time: the thermocouple embedded in the charging cable connector, the NTC thermistor of the device shell, and the internal temperature of the battery obtained from the BMS; Intelligent control: The host MCU compares and calculates the above-mentioned multi-source temperature data with the temperature and current characteristic matrix pre-set in the system. According to the calculation result, the PWM control signal of the programmable power output module is dynamically adjusted, so as to change the output charging current, for example, automatically preheat the battery with small current at low temperature, and automatically reduce the current to limit the temperature rise at high temperature, realizing all-weather adaptive charging without additional hardware assistance; Safety and repair control: The system makes safety judgment according to the SOH value obtained by independent evaluation. If the battery health is lower than the pre-set safety threshold, the charging is stopped immediately and an alarm is given. In addition, the system can start the repair pulse charging mode according to the instruction or pre-set condition, control the power module to output high-energy pulses with specific voltage, current, frequency and duty cycle, for repairing the reversible damage such as sulfuration of the battery.
[0030] 3. Working principle of wide voltage input and power adaptation The front-end power module adopts a topology structure containing active PFC and LLC resonant converter, which can work efficiently and stably under a wide range of AC input voltage of 85V-265V, output a stable DC bus voltage. More importantly, the host MCU monitors the input voltage state in real time, and adjusts the subsequent charging power strategy according to the state, to ensure that the overall energy efficiency of the system remains optimal under different power grid conditions, realizing intelligent linkage of the power module and the charging management system.
[0031] 4. Working principle of multi-protocol BMS communication and parallel management This function enables a battery testing and management machine to simultaneously connect and manage multiple battery devices of different brands: Automatic identification and matching: The Bluetooth module of the device continuously scans the surrounding environment. When receiving the Bluetooth broadcast packet sent by the BMS, the host MCU analyzes the data in the broadcast packet and extracts the unique feature identification code representing the BMS brand or model. Then, the MCU quickly matches in the locally pre-stored identification code and communication instruction set protocol library. Once a successful match is made, the complete communication protocol is automatically called; Parallel connection and data exchange: The device uses a Bluetooth SOC chip that supports multi-connection features as the hardware foundation. At the software level, through multiplexing mechanism, the host MCU can simultaneously maintain GATT connection with multiple matched BMSs and perform data exchange with each BMS in sequence but at high frequency, reading its cell voltage, temperature, SOC, SOH, and other detailed information; Data aggregation and uploading: The host MCU acts as a data hub, uniformly analyzes, formats, and temporarily stores the heterogeneous data obtained from various BMSs and its own detection modules. Then, it integrates all the data into a standardized aggregated data packet. Finally, through the unique Bluetooth connection channel between the device and the phone APP, it uploads the multi-device information to the APP, and the user can monitor the status of all connected batteries on one interface of the APP.
[0032] It should be noted that, in this text, relational terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without further limitation, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.
Claims
1. A wide voltage adaptive multi-mode programmable charging and testing all-in-one machine, characterized in that: The charger includes a master MCU, a wide voltage input AC-DC conversion module, a programmable power output module, a battery state detection module, a temperature sensing module, a wireless communication module, and a load relay. The temperature sensing module includes a thermocouple arranged at a charging cable connector and an NTC thermistor arranged at a device housing. The wireless communication module is a low-power Bluetooth (BLE) communication module. The load relay is connected between the charger and a battery and is controlled by the master MCU. The charger includes an independent working mode and a BMS communication cooperative mode. In the independent working mode, the master MCU is configured to: control the load relay to be disconnected, so that the battery is in a resting state, and sample an open circuit voltage (OCV) of the battery after resting by a high-precision ADC in the battery state detection module; query an OCV-SOC comparison table for different battery types pre-stored in a memory according to the sampled OCV value, and obtain an initial SOC estimation value; in a subsequent charging process, correct the initial SOC estimation value by closed-loop feedback based on an integral of a charging current with respect to time; in a pre-charging phase, calculate a dynamic internal resistance of the battery by rapidly adjusting a voltage and a current and using a high-speed current-voltage response curve, compare a current DCR value with a pre-stored nominal internal resistance of the battery in a brand-new state, and normalize the current DCR value to obtain a battery state of health (SOH) evaluation value; In the BMS communication cooperative mode, the master MCU is further configured to: establish a connection with a BMS through the wireless communication module and obtain battery data, and use the battery data to autonomously learn and correct the OCV-SOC comparison table.
2. The wide voltage adaptive multi-mode programmable charge and test all-in-one machine of claim 1, wherein: The master MCU is further configured to query a pre-stored temperature and current characteristic matrix according to multi-source temperature data collected by the temperature sensing module, dynamically adjust a charging current, and implement a battery self-preheating function in a low-temperature environment and a current limiting protection function in a high-temperature environment.
3. The wide voltage adaptive multi-mode programmable charge and test all-in-one machine of claim 1, wherein: The master MCU is further configured to execute a repair pulse charging mode to generate a pulse output with specific voltage, current, frequency, and duty cycle.
4. The wide voltage adaptive multi-mode programmable charge and inspection all-in-one machine of claim 1, wherein: The master MCU is further configured to determine a battery health degree according to the SOH evaluation value, and stop a charging process and issue an alarm if the SOH evaluation value is lower than a pre-set safety threshold.
5. The wide voltage adaptive multi-mode programmable charge and inspection all-in-one machine of claim 1, wherein: The wireless communication module uses a multi-mode Bluetooth SOC chip supporting a multi-connection feature, a memory of the charger pre-stores characteristic identification codes of multiple BMS brands and corresponding communication instruction sets, and the master MCU is configured to scan and analyze the characteristic identification codes in a BMS broadcast packet in the surrounding area, match the analyzed characteristic identification codes with a local protocol library, and automatically call a corresponding communication instruction set to establish a GATT connection with a target BMS and perform data interaction if the matching is successful.
6. The wide voltage adaptive multi-mode programmable charge and inspection all-in-one machine of claim 1, wherein: The master MCU is configured to maintain GATT connections with multiple BMSs simultaneously and perform data exchange with each connected BMS in a time slice polling or event triggering manner through a multiplexing mechanism of a software stack.
7. The wide voltage adaptive multi-mode programmable charge-inspection all-in-one machine according to claim 1, wherein: The charge and inspection integrated machine supports online updating and expansion of the pre-stored BMS communication protocol library in the memory through an external device.
8. The wide voltage adaptive multi-mode programmable charge-inspection all-in-one machine according to claim 1, wherein: The master MCU is configured to receive and parse heterogeneous data from multiple connected BMS, format and aggregate the parsed data, and upload the aggregated data packet to a mobile phone APP through a single Bluetooth connection.
9. The wide voltage adaptive multi-mode programmable charge-inspection all-in-one machine according to claim 1, wherein: The wide-voltage-input AC-DC conversion module includes an active power factor correction circuit and an LLC resonant converter.
10. The wide voltage adaptive multi-mode programmable charge-inspection all-in-one machine according to claim 1, wherein: The programmable power output module adopts a phase-shifted full-bridge topology structure, and the master MCU outputs a modulatable PWM signal which is converted into an analog direct-current voltage through an RC low-pass filter circuit.