Intelligent charging equalization method of intelligent charging equalization system based on cloud data exchange

Abstract

The present invention discloses an intelligent charging equalization method of an intelligent charging equalization system based on cloud data exchange. The intelligent charging equalization system includes a host terminal, a Cloud brain, a ZUCC‑IOT cloud, a charging equalization device, a mobile phone APP terminal, a battery pack to be charged and a driving vehicle thereof. The intelligent charging equalization method includes the following steps: the charging equalization device scans the battery pack to verify the rationality of the identity. After the identity authentication is successful, the battery pack and the charging equalization device establish a CAN communication connection, evaluate the health information of the battery pack, and warn of abnormal cells not to charge when necessary; for battery packs that have passed the health assessment, the Cloud brain intelligently matches the charging and balancing strategies for the battery in combination with the health status of the battery; the charging equalization device starts to be electrically connected to the battery to charge and balance the battery pack. The present invention proposes intelligent screening of abnormal batteries before charging begins, intelligent matching of charging equalization strategies, and achieves battery health information tracking throughout its life cycle, thereby extending the battery service life.

Description

[Technical field]

[0001] The present invention relates to the technical field of charging new energy lithium-powered electric two-wheeled vehicles, and in particular to the technical field of an intelligent charging equalization method of an intelligent charging equalization system based on cloud data exchange. [Background technology]

[0002] Excellent acceleration performance and long-lasting cruising range are expected by the performance development of electric two-wheeled vehicles and motorcycles, which are inseparable from the capacity, voltage and reliability of power batteries. Unlike electric vehicles, the batteries of electric two-wheeled vehicles and motorcycles are designed to work in pairs or more sub-packs, which can be easily taken out of the vehicle for charging or replacement. The higher the battery pack voltage, the smaller the electrical loss, but the safety requirements of the electrical design also increase. Therefore, the voltage of general electric two-wheeled vehicles is limited to 256V. The battery pack voltage determines the number of cells in series; further, the number of parallel cells can be defined according to the battery power determined by the acceleration and cruising range of the whole vehicle. Due to differences in the factory status of the cells, differences in the working environment and differences in the degree of cell aging, the imbalance problem between cells is becoming increasingly prominent. The manifestations of cell imbalance are mainly reflected in voltage, power and resistance. Related studies have shown that a 20% difference in battery internal resistance will lead to a 40% inconsistent capacity attenuation. BMS uses the cell that is charged first as the reference for the end of charging of the entire battery pack (pack). It can be said that the maximum effective capacity of the entire battery pack depends on the cell with the smallest effective capacity, and the barrel effect of the cell is very prominent. If the differences between batteries are not balanced, the inconsistency between the cells will gradually expand during use, causing the inconsistency of the lithium-ion battery pack to expand. Especially for electric two-wheeled vehicles, because they adopt the form of multiple packs, the balance between packs is difficult to control, and the balance problem between packs of different batches is more prominent.

[0003] The Chinese patent with the publication number CN112018837A proposes a battery balancing device that supports multi-channel isolation and parallel connection, which makes up for the limitations of existing balancing devices, supports high-rate current to charge and balance the battery module, uses the MCU module to complete the CAN communication and control functions, and can control the device through the host computer. The host computer transmits control signals to the battery balancing circuit through the CAN communication module to modify the control parameters. The invention divides the series battery group into multiple groups of standard batteries (which can be single cells or modules formed by multiple cells in parallel) and balances them separately. The standard batteries are balanced using a DC / DC with controllable output current. The balancing algorithm is a voltage-based balancing. It is speculated that the battery cell is directly charged at the maximum voltage allowed. All balancing assessment indicators are voltage, and the differences in ampere-hours and capacity between batteries are not considered, and the balancing of the entire battery life cannot be covered.

[0004] The Chinese patent with publication number CN112026587A determines whether to perform current limiting balancing control or active balancing control based on the state of charge of each single cell and the average state of charge of each single cell in the battery pack. A balancing management module comprising multiple balancing units is proposed, each balancing unit comprising multiple single cells, a switch matrix module and a transformer. The balancing algorithm is a SOC-based balancing method, which collects the current and voltage information of each battery cell through voltage and current sensors. The invention does not clearly point out the combination method of balancing cells. A four-wheel electric vehicle usually has thousands of batteries. The entire system is very large, and the balancing cost is also high, which makes it difficult to implement.

[0005] The existing technology has the following defects:

[0006] 1. For two-wheeled electric vehicles, fast battery charging and battery replacement solutions make it possible to have a long battery life, which puts forward requirements for the design and development of battery packs: the size and weight of the battery pack cannot be too large; at the same time, the acceleration and climbing driving performance in driving conditions require a large current and high power source output, which requires the battery pack to have a large enough capacity. Based on the above two points, developers often use a combination of two or even more batteries. Single batteries are easy to disassemble and carry, and the overall capacity is guaranteed, but this leads to the problem of balancing multiple battery packs;

[0007] 2. Existing battery balancing algorithms usually use the cell voltage or SOC as the trigger condition for turning on or off balancing. After battery aging, the mapping relationship between the open circuit voltage OCV and SOC changes, which leads to inaccurate SOC estimation and deviations in the judgment of battery charge and discharge start and end, which ultimately affects the overall charge and discharge performance of the battery.

[0008] 3. The current mainstream balancing is passive balancing, which reduces the useful power conversion of the battery, takes a long time to balance, and has the problem of overheating. It is not a mainstream development trend. Active balancing has high hardware development costs and increases space requirements. If the balancing circuit is placed on the battery side of each battery pack, it is not feasible for electric two-wheeled vehicles.

[0009] 4. Currently, the development of balancing equipment is based on batteries of the same brand, which is a one-to-one development, and the development cost of balancing equipment is high.

[0010] To this end, in view of the characteristics of the battery cell layout of electric two-wheeled vehicles, the present invention proposes an intelligent charging balancing system and operation method based on cloud data exchange, so as to ensure the reliable operation of the battery pack of the two-wheeled vehicle throughout its life cycle at an acceptable cost. Based on big data records, the system intelligently screens the rechargeable battery packs, provides an accurate voltage-charge function relationship, and carries out targeted charging and balancing of the battery packs, providing a solution for the safe and controllable operation of the battery pack throughout its life cycle. [Summary of the invention]

[0011] The purpose of this invention is to solve the problems in the prior art, the technical problems of existing battery balancing and the safety management problems of electric two-wheeled vehicle operation, and propose an intelligent charging balancing method based on cloud data exchange for intelligent charging balancing system, which actively updates the charging balancing strategy during the whole life cycle, which is very novel; ensure the international leading position of the company's independent development in the field of electric two-wheeled vehicles (expanded to three-wheeled vehicles); carry out general charging and charging balancing dual modes in parallel and intelligent charging balancing in combination with actual operation conditions. Focusing on systematic design and early layout is conducive to controlling development costs and promoting the industrialization and commercialization of this technology.

[0012] To achieve the above-mentioned purpose, the present invention proposes an intelligent charging balancing system based on cloud data exchange, including a host terminal, a Cloud brain, a ZUCC-IOT cloud, a charging balancing device, a mobile phone APP terminal, a battery pack to be charged and a driving vehicle thereof; the host terminal is responsible for the maintenance and update of battery charging and balancing strategies, and uploads information to the Cloud brain; the Cloud brain is used to make decisions on the charging balancing strategy of the battery to be charged, and sends the latest battery pack charging balancing strategy to the ZUCC-IOT cloud, and the Cloud brain and the mobile phone APP terminal perform two-way interaction on the charging balancing status; the ZUCC-IOT cloud is used to communicate with the charging balancing device and the driving vehicle, and is used to collect the health status information of the battery to be charged; the charging balancing device establishes a communication connection and an electrical connection with the battery to be charged, and is used to carry out charging and balancing work of the battery to be charged.

[0013] Preferably, the Cloud brain adopts different charging balancing strategies for battery packs to be charged with different health levels, specifically: the charging balancing device collects freeze frame information of the battery pack to be charged and uploads it to the ZUCC-IOT cloud; the ZUCC-IOT cloud communicates with the driving vehicle and obtains driving vehicle fault information; the Cloud brain evaluates the battery operation full life health information sent by the ZUCC-IOT cloud, communicates with the host terminal, and selects the most matching charging and balancing strategy and sends it to the ZUCC-IOT cloud.

[0014] Preferably, the charging equalization device is mainly composed of a PWM generator, a resonant converter and a voltage multiplier. The charging equalization device is used to achieve the balance of the cells in the battery module or the cells in parallel (small module). The charging equalization device is used to achieve the balance within the module (or 7 strings of cells, nominal voltage 3.6v) or between modules (also called large module, nominal voltage 25.2v); the equalization device does not need to be arranged with cell-level voltage detection and current detection devices, further reducing the cost of the intelligent charging equalization system; the battery pack to be charged is provided with three connector interfaces, namely a standard charging interface, a fast charging interface and a balancing interface, and each interface is designed with a mechanical self-locking structure, and the electrical connection requires a logic switch in addition to the physical connection to achieve.

[0015] The present invention also proposes an intelligent charging equalization method of an intelligent charging equalization system based on cloud data exchange, comprising the following steps:

[0016] Step 1: Connect the battery pack to be charged to the charge equalization device;

[0017] Step 2: Scan the QR code through the APP for identity authentication;

[0018] Step 3: After successful identity authentication, the battery pack to be charged completes the CAN or UDS communication connection with the charge balancing device, and the health status information of the battery pack to be charged is read into the charge balancing device, which is specifically reflected in the battery pack freeze frame data stored in the battery pack management system BMS; ZUCC-IOT cloud reads the battery pack freeze frame data from the charge balancing device in the format specified by the ZUCC-IOT protocol-D protocol; ZUCC-IOT cloud uploads the data to the Cloud brain in the format specified by the ZUCC-IOT protocol-U protocol; Cloud brain communicates with the driving vehicle, queries the vehicle fault information record, and summarizes, processes and analyzes the battery pack data information; the Cloud brain summarizes and processes the freeze frame and vehicle fault information, and conducts battery pack cell health information assessment. When the abnormal alarm threshold is reached, the Cloud brain will start the abnormal battery pack processing mechanism, cut off subsequent charging actions, and transmit the corresponding information to the management platform; when the cell health information is judged to be normal and the battery pack is ready for charging, it proceeds to the next step;

[0019] Step 4: The Cloud Brain communicates with the host terminal, intelligently matches the charging and balancing strategies according to the battery health, and the Cloud Brain sends the latest charging and balancing strategies to the ZUCC-IOT cloud in the communication format specified by the ZUCC-IOT protocol-U, and the ZUCC-IOT cloud sends the charging and balancing strategies to the charging balancing device in the communication format specified by the ZUCC-IOT protocol-D;

[0020] Step 5: The charging and balancing device performs charging and balancing in sequence; further, after the battery pack is charged, if the balancing condition is met, the charging and balancing device automatically starts the battery balancing, and the user can also choose to turn off or on the balancing action.

[0021] Preferably, the judgment basis of step 2 is the uniqueness of the binding between the battery to be charged and the identity of the vehicle it drives.

[0022] Preferably, the basic information of the freeze frame in the step 3 includes the unique code of the battery pack ID (battery cell level), the number of completed charge and discharge cycles, the operating time, the high-rate discharge time, the maximum discharge current, the historical highest temperature (battery cell level), the historical lowest temperature (battery cell level), the historical highest voltage (battery cell level), the historical lowest voltage (battery cell level), the battery SOC value stored at the last power outage, and the absolute time of the power outage; the ZUCC-IOT protocol-D and ZUCC-IOTprotocol-U in the step 3 are one of MQTTS or HTTPS, the data is encrypted using SSL or TLS, and the data is packaged and transmitted in one of the GPB format, JSON format or XML format.

[0023] Preferably, the charging action in step 4 is performed in four stages: pre-charging 1, pre-charging 2, constant current charging, and constant voltage charging; the battery balancing is automatically turned on in the late second stage or the third stage of charging, and the user can also decide to turn on or off the balancing.

[0024] Preferably, in step 5, the battery pack SOC (state of charge) is used as the evaluation basis for charging termination, and the charge equalization system dynamically updates the OCV-SOC calculation method in real time according to the battery operating state SOH.

[0025] Preferably, the balancing in step 5 is divided into intra-group balancing and inter-group balancing. The inter-group balancing of the battery modules uses the SOC deviation as the balancing start and stop condition. The intra-module balancing is automatically turned on and conditionally turned off through circuit settings. By selecting a suitable SOC termination condition, the end time of the inter-group balancing (nominal voltage 25.2v) is earlier than the intra-group (small module, nominal voltage 3.6v) balancing, ensuring that the balancing is fast and effective.

[0026] As a preferred method, in view of the fact that the battery module of an electric two-wheeled vehicle is arranged with 7 strings of cells (or small modules, with a nominal voltage of 3.6v) as the basic unit, a programmable switch array is used to carry out balancing between modules (large modules, with a nominal voltage of 25.2v), and active balancing within the battery pack within the voltage range of 350v can be performed. A set of intelligent charging and balancing equipment can be used to charge and balance battery packs of multiple specifications or even multiple brands, breaking the one-to-one binding relationship between battery balancing equipment and battery module design.

[0027] Preferably, the specific algorithm for determining the open circuit voltage OCV and SOC of the battery pack in step 5 is as follows: read the cell freeze frame information of the battery pack, extract the absolute time of the most recent power-off moment of the battery pack, the SOC value, the number of completed charge and discharge cycles, etc. Chg The number is less than the threshold Th Ch g, and the standing time t idl >OCV static judgment threshold Th idl , the open circuit voltage V_OCV of the battery pack is used as the battery voltage V_Bat, and the SOC is obtained through the OCV-SOC function relationship f1 (SOV, OCB); if the rest time is less than the OCV rest time threshold, the SOC recorded in the most recent power-off record is used as the initial charging SOC, and the real-time SOC estimation is performed based on the ampere-hour integration method while the voltage at the end of constant current charging is used as a judgment. If the SOH degradation coefficient of the battery pack decreases by more than 10%, the SOC and OCV relationship must be re-measured, and the battery charge capacity must be re-evaluated, and the battery charging balancing strategy is updated accordingly.

[0028] For t>0, that is, during the charging process, the SOC is calculated using the ampere-hour integration method.

[0029]

[0030] Where I is the total battery charging current (charging is negative and discharging is positive), and γ is the charging efficiency.

[0031] The present invention implements hierarchical balancing between series-connected cells and modules, and is designed for the voltage platform of electric two-wheeled vehicles. Each battery pack is composed of n modules in series, preferably n=1, 2, 3, 4, 5, 6. . . 14; each module is composed of 7 strings of single cells or cells connected in parallel and then in series. And by setting the balancing opening and closing conditions, the adequacy of the balance between groups is ensured. This method has the advantages of simple operation, low balancing power, low balancing cost, and short time consumption.

[0032] Beneficial effects of the present invention:

[0033] 1. The present invention is designed for the characteristics of the battery pack of electric two-wheeled vehicles. It can conveniently realize the balance within and between modules of the battery module with 7 series-connected cells, and can perform active balance within the battery pack within the voltage range of 350V; it meets the topological structure design of the battery pack of electric two-wheeled vehicles. One charging equalization device can be used for charging and balancing battery packs of different models, and has good compatibility.

[0034] 2. The present invention provides a method and system for real-time updating of balancing strategies based on a CLOUD cloud server. By reading the BMS freeze frame of the battery to be charged and the fault information of the entire vehicle, the battery health information can be evaluated, and abnormal cells can be disconnected from the charging balancing circuit, thereby ensuring safe and efficient charging.

[0035] 3. The present invention provides a solution for real-time calibration of the functional relationship between the battery state of charge SOC and the open circuit voltage OCV throughout the entire life cycle, providing accurate battery charge capacity throughout the entire life cycle, avoiding overcharging and over-discharging of the battery, and providing an accurate reference for battery charging and endurance management and cruising range calculation.

[0036] 4. The present invention has developed an active balancing circuit composed of a PWM generator, a resonant circuit and a voltage multiplier, which can actively start the balancing of the battery cell units in series, and can also be controlled by the user through an APP, thereby providing differentiated charging services.

[0037] 5. The present invention is a hierarchical balancing method implemented between series-connected cells and modules. It is designed for the voltage platform of electric two-wheeled vehicles. Each battery pack is composed of n modules in series (generally for ternary lithium batteries, the nominal voltage is 25.2v*12=302.4), preferably n=1,2,3,4,5,6. . . 14; each module is composed of 7 strings of single cells or cells connected in parallel and then in series (generally for ternary lithium batteries, the nominal voltage is 3.6v*7=25.2v). Compared with the current mainstream solution of directly connecting the battery pack to the balancing equipment, this method has the advantages of simple operation, low balancing power, low balancing cost, and short time consumption.

[0038] The features and advantages of the present invention will be described in detail through embodiments in conjunction with the accompanying drawings.

Brief Description of the Drawings

[0039] Figure 1 It is a schematic diagram of the ZUCC intelligent battery exchange balancing system of the intelligent charging balancing method of the intelligent charging balancing system based on cloud data exchange of the present invention;

[0040] Figure 2 It is a smart battery swapping and balancing flow chart of a smart charging balancing method of a smart charging balancing system based on cloud data exchange of the present invention;

[0041] Figure 3 It is a four-stage charging principle diagram of pre-charging 1->pre-charging 2->constant current charging->constant voltage charging of the intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange of the present invention;

[0042] Figure 4It is a schematic diagram of the electrical connection of the equalization circuit of the intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange of the present invention, mainly involving the equalization between battery modules;

[0043] Figure 5 It is an electrical schematic diagram of the equalization of the intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange of the present invention, mainly involving equalization within the battery module;

[0044] Figure 6 The equalization circuit equalization waveform timing diagram of the intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange of the present invention;

[0045] Figure 7 It is a calculation block diagram of the SOH degradation coefficient evaluation of the intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange of the present invention. [Specific implementation method]

[0046] like Figure 1 As shown, the present invention includes a charging equalization device, a ZUCC-IOT cloud, a host terminal, a Cloud brain, and a mobile phone APP terminal, a battery pack to be charged and a vehicle driven by it. The ZUCC-IOT cloud communicates with the charging equalization device and the driven vehicle to collect the health status information of the battery to be charged; the charging equalization device establishes a communication connection and an electrical connection with the battery to be charged to carry out the charging and equalization work of the battery to be charged; the host terminal is responsible for the maintenance and update of the battery charging and balancing strategy, and uploads the information to the Cloud cloud; the Cloud cloud makes decisions on the charging equalization strategy of the battery to be charged, and sends the latest battery pack charging strategy to ZUCC-IOT; at the same time, the Cloud brain and the APP terminal perform two-way interaction on the charging equalization status. The charging equalization device is used to charge and equalize the battery pack to be charged. The battery pack is provided with three connector interfaces, and the connector interfaces of the battery pack are respectively a ZUCC standard charging interface, a fast charging interface and a balancing interface, and the connector interfaces are designed with a mechanical self-locking structure. The ZUCC standard charging interface is used to provide conventional charging support, and the ZUCC standard charging interface is composed of a high-voltage power supply inlet V high +、V high -, low-voltage power supply and CAN communication port; the balancing interface is led out from both ends of each module of the battery pack (nominal voltage 25.2v), and also includes a CAN communication port.

[0047] The present invention also includes an intelligent charging equalization method, such as Figure 2 As shown, the specific steps are:

[0048] Step 1: Connect the battery pack to be charged to the charge equalization device;

[0049] Step 2: Scan the QR code through the APP for identity authentication;

[0050] Step 3: After successful identity authentication, the battery pack to be charged completes the CAN or UDS communication connection with the charge balancing device, and the health status information of the battery pack is read into the charge balancing device, which is specifically reflected as the freeze frame data stored in the battery pack management system BMS; the ZUCC-IOT cloud reads the battery pack freeze frame information from the charge balancing device in the format specified by the ZUCC-IOT protocol-D protocol; the ZUCC-IOT cloud uploads the data to the Cloud Brain in the format specified by the ZUCC-IOT protocol-U protocol. The Cloud Brain communicates with the battery-driven vehicle to query the vehicle fault information record; the battery pack data information is aggregated, processed and analyzed; the Cloud Brain aggregates and processes the freeze frame and vehicle fault information, and conducts an assessment of the battery pack's cell health information. When the abnormal alarm threshold is reached, the Cloud Brain will activate the abnormal battery pack processing mechanism, cut off subsequent charging actions, and transmit the corresponding information to the management platform. When the cell health information is judged to be normal and the battery pack is rechargeable, it proceeds to the next step;

[0051] Step 4: The Cloud Brain communicates with the host terminal, intelligently matches the charging and balancing strategies according to the battery health, and the Cloud Brain sends the latest charging and balancing strategies to the ZUCC-IOT cloud in the communication format specified by the ZUCC-IOT protocol-U, and the ZUCC-IOT cloud sends the charging and balancing strategies to the charging balancing device in the communication format specified by the ZUCC-IOT protocol-D;

[0052] Step 5: The charging and balancing device performs charging and balancing in sequence. Furthermore, after the battery pack is charged, if the balancing condition is met, the charging and balancing device automatically starts the battery balancing, and the user can also choose to turn off or on the balancing action.

[0053] Specifically, the basis for determining the identity authentication in step 2 is the uniqueness of the identity binding between the battery to be charged and the vehicle it drives, which is obtained by scanning the battery pack and the unique identifier of the driving vehicle through the offline terminal (EOL), and uploading the identification data to the host terminal through WIFI wireless communication.

[0054] Specifically, the protocols of ZUCC-IOT protocol-D and ZUCC-IOT protocol-U in steps 3 and 4 are one of MQTTS or HTTPS, the data is encrypted using SSL or TLS, and the data is packaged and transmitted in a GPB format, a JSON format, or an XML format.

[0055] Specifically, Figure 3As shown, the charging action in step 5 is carried out in four stages: pre-charge 1, pre-charge 2, constant current, and constant voltage. In the pre-charge 1 stage, the battery is passed through a small voltage to detect the battery cell, which is an auxiliary means of detecting the health status of the battery cell. The formal charging stage of the battery is carried out in the order of pre-charge 2, constant current, and constant voltage charging.

[0056] Specifically, the basic information of the freeze frame in step 3 includes the battery unique code, number of charge and discharge cycles, operating time, high-rate discharge time, historical highest temperature, historical lowest temperature, highest discharge current, battery SOC at the last power outage, and the absolute time of the power outage.

[0057] Specifically, the battery pack health information assessment in step 3 integrates the freeze frame data and the historical fault information records of the whole vehicle driven by the battery pack, including battery cell temperature monitoring, voltage sampling failure, current sampling failure, SOC jump information, etc.

[0058] Specifically, the present invention is a hierarchical balancing implemented in series cells (modules), and the electrical connection of the charge balancing in step 5 is as follows: Figure 4 As shown. For the voltage platform design of electric two-wheeled vehicles, each battery pack is composed of n modules connected in series (generally for ternary lithium batteries, the nominal voltage is 25.2v*12=302.4), preferably n=1,2,3,4,5,6. . . 14; each module is composed of 7 strings of single cells or cells connected in parallel and then in series (generally for ternary lithium batteries, the nominal voltage is 3.6v*7=25.2v). Figure 4 As shown, each module is equipped with a voltage monitoring unit, and there are n voltage monitoring units in a battery pack, and 1 current monitoring unit in the battery pack. The positive and negative poles of each module are respectively connected to the programmable electrical connection port column. The balancing management unit selects modules with significant voltage deviation according to the module voltage, and the total number is n / 2, generally not more than 7. Furthermore, the positive and negative poles of these modules can be conveniently output to the balancing module from the programmable electrical connection port.

[0059] Further, to ensure the efficiency of balancing, the present invention defines the conditions for enabling and disabling balancing, ensuring that the end time of inter-group balancing is earlier than that of intra-group balancing. Conditions for enabling inter-module balancing: 1. Entering the late stage of constant-current charging; 2. The SOC difference between modules is greater than 15%; 3. Selecting the battery pack with the largest SOC deviation for balancing; 4. The average temperature difference between modules < system allowable temperature deviation + 5°C. Conditions for disabling balancing: 1. SOC difference < 5%; 2. The change value of the balancing difference within 1 hour is less than 1%; 3. The temperature difference between modules > system allowable temperature deviation + 10°C; For electric two-wheelers, the cooling method of the battery pack is mainly air-cooling, and the uniformity of the temperature field distribution of the battery cells is not very ideal. Implementing zoned battery balancing in combination with the actual working environment of the battery is particularly important for battery balancing using air-cooling in electric two-wheelers and the like.

[0060] Specifically, as Figure 5 shown is the electrical principle model of battery charging balancing, which consists of a PWM generator, a resonant unit, and a voltage multiplier. In this example, the number of battery cells or modules to be monitored is 7. Specifically, it includes: CMOS transistors Q1, Q2, body diodes D1, D2, parasitic capacitors C1, C2, resonant inductor L r , transformer magnetization inductor L m , resonant inductor C r , battery cells to be balanced (intra-module balancing) or modules (inter-module balancing) B1, B2…B7, D 11 , D 12 , D 21 , D 22 ...D 17 , D 27 , rectifier diodes, C 11 , C 12 , C 21 , C 22 ...C 17 , C 27 , rectifier capacitors.

[0061] Specifically, Figure 6 shows the timing logic diagram of the balancing circuit working:

[0062] When t0 ≤ t < t1, Q1 is driven to turn on, the inductor Lm starts to resonate, and the transformer excitation current increases linearly. At this time, the current direction is defined as positive. When i Lr > i Lm , the transformer secondary side outputs current, and the current flows through the diode D i1 to charge the capacitor C i1 (i = 1, 2,..7). When i Lm = i Lr , the charging stops;

[0063] When \(t1\leq t\lt t2\), Q1 remains open and Q2 remains closed, \(i\) Lr \(<i\) Lm The current of the transformer reverses,

[0064] Discharge cutoff (\(i = 1,2,..7\));

[0065] When \(t2\leq t\lt t3\), except for the battery filter capacitor, \(i\) Lr \(=i\) Lm , \(i\) Lr follows \(i\) Lm continues to increase linearly and there is no current on the secondary side of the transformer.

[0066] When \(t3\leq t\lt t4\), Q2 is driven to open and the exciting current \(i\) Lm begins to decrease linearly, \(L\) r , \(C\) r begins to resonate, the secondary side continuously outputs current, and the capacitor \(C\) i1 discharges to the battery module (or cell) through the diode \(D\) i2 until \(i\) Lm \(=i\) Lr。

[0067] When \(t4\leq t\lt t5\), Q2 remains on and Q1 remains off, the current on the secondary side becomes positive again, and the current flows through the diode \(D\) i1 to charge the capacitor \(C\) i1 (\(i = 1,2,..7\)), when \(i\) Lm \(=i\) Lr the charging stops;

[0068] This cycle continues until the cells reach balance again.

[0069] Specifically, as Figure 7 shown, the calculation of the battery health information SOH degradation factor can be quantitatively analyzed from 4 dimensions, specifically including the high-rate discharge load of the cell, the extreme cell temperature, the extreme cell voltage, the service life, and the monitoring of the battery operation boundary, etc. Further, the degradation factor coefficient is obtained based on model calculation, using the test data in the battery development and test stage as the basis, and with the help of modeling and simulation tools. For example, the mbc toolbox of matlab can be used for test data fitting and modeling.

[0070] Specifically, the specific algorithm for determining the open-circuit voltage OCV and SOC of the battery pack in step 5 is as follows: Read the frozen frame information of the cells in the battery pack, extract the absolute time, SOC value, and the number of completed charge and discharge cycles of the battery pack at the moment of the last power-off. If the number of charge and discharge cycles \(N\) ChgThe number is less than the threshold Th Chg , and the standing time t idl >OCV static judgment threshold Th idl , with the battery pack open circuit voltage V_ OCV As the battery voltage V Bat , SOC is obtained through the OCV-SOC function relationship f1(SOV,OCB); if the rest time is less than the OCV rest time threshold, the SOC recorded in the most recent power-off state is used as the initial charging SOC, and the real-time SOC estimation is performed based on the ampere-hour integration method while the voltage at the end of constant current charging is used as a judgment. If the SOH degradation coefficient of the battery pack decreases by more than 10%, the SOC and OCV relationship must be re-measured, and the battery charge capacity must be re-evaluated, and the battery charge balancing strategy must be updated accordingly.

[0071] if N Chg <Th Chg &t idl >Th idl ,V Bat =V OCV ,SOC0=f1(SOC,OCV),

[0072] if N Chg <Th Chg &t idl <Th idl ,SOC0=SOC sav ;

[0073] For t>0, that is, during the charging process, the SOC is calculated using the ampere-hour integration method.

[0074]

[0075] Where I is the total battery charging current (charging is negative, discharging is positive), γ is the charging efficiency,

[0076] if N Chg >Th Chg &&ΔDF SOH >10%, recalibrate f(SOC,OCV).

[0077] At present, the research and development level of lithium batteries and their management systems for electric two-wheeled vehicles in my country varies greatly. If supervision is not in place, there will be high safety risks in long-term use. The present invention proposes intelligent screening of abnormal batteries before charging begins, intelligent matching of charging balancing strategies, and tracking of battery health information throughout its life, thus extending the battery life. The system can be put into use in a public and shared form with controllable costs.

[0078] The above embodiments are intended to illustrate the present invention, not to limit the present invention. Any solution that is a simple transformation of the present invention belongs to the protection scope of the present invention.

Claims

1. An intelligent charging equalization method of an intelligent charging equalization system based on cloud data exchange, characterized in that: The intelligent charging and balancing system based on cloud data exchange includes a host terminal, a Cloud brain, a ZUCC-IOT cloud, a charging and balancing device, a mobile phone APP terminal, a battery pack to be charged and a driving vehicle thereof; the host terminal is responsible for the maintenance and update of battery charging and balancing strategies, and uploads information to the Cloud brain; the Cloud brain is used to make decisions on the charging and balancing strategies of the batteries to be charged, and sends the latest battery pack charging and balancing strategies to the ZUCC-IOT cloud, and the Cloud brain and the mobile phone APP terminal perform two-way interaction on the charging and balancing status; the ZUCC-IOT cloud is used to communicate with the charging and balancing device and the driving vehicle, and to collect the health status information of the battery to be charged; the charging and balancing device establishes a communication connection and an electrical connection with the battery to be charged, and is used to carry out the charging and balancing work of the battery to be charged; The intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange includes the following steps: Step 1: Connect the battery pack to be charged to the charge equalization device; Step 2: Scan the QR code through the mobile APP for identity authentication; Step 3: After the identity authentication is successful, the battery pack to be charged completes the CAN or UDS communication connection with the charge balancing device, and the health status information of the battery pack to be charged is read into the charge balancing device, which is specifically reflected in the battery pack freeze frame data stored in the battery pack management system BMS; ZUCC-IOT cloud reads the battery pack freeze frame data from the charge balancing device in the format specified by the ZUCC-IOT protocol-D protocol; ZUCC-IOT cloud uploads the data to the Cloud Brain in the format specified by the ZUCC-IOT protocol-U protocol; Cloud Brain communicates with the driving vehicle, queries the vehicle fault information record, and summarizes, processes and analyzes the battery pack data information; the Cloud Brain summarizes and processes the freeze frame and vehicle fault information, and conducts battery pack cell health information assessment. When the abnormal alarm threshold is reached, the Cloud Brain will start the abnormal battery pack processing mechanism, cut off the subsequent charging action, and transmit the corresponding information to the management platform; when the cell health information is judged to be normal and the battery pack is ready for charging, it proceeds to the next step; Step 4: The Cloud Brain communicates with the host terminal, intelligently matches the charging and balancing strategies according to the battery health, and the Cloud Brain sends the latest charging and balancing strategies to the ZUCC-IOT cloud in the communication format specified by the ZUCC-IOT protocol-U, and the ZUCC-IOT cloud sends the charging and balancing strategies to the charging balancing device in the communication format specified by the ZUCC-IOT protocol-D; Step 5: The charging and balancing device performs charging and balancing in sequence; further, after the battery pack is charged, if the balancing condition is met, the charging and balancing device automatically starts the battery balancing, and the user can also choose to turn off or on the balancing action; In step 5, the battery pack SOC is used as the evaluation basis for charging termination, and the charge equalization system dynamically updates the OCV-SOC calculation method in real time according to the battery operating state SOH; The balancing in step 5 is divided into intra-group balancing and inter-group balancing. The inter-group balancing of the battery modules uses the SOC deviation as the balancing on and off condition. The intra-battery module balancing is automatically turned on and conditionally turned off through circuit settings. Conditions for enabling balancing between modules:

1. Charging enters the late stage of constant current charging; 2. The SOC difference between modules is greater than 15%; 3. Select the battery pack with the largest SOC deviation for balancing; 4. The average temperature difference between modules < the system allowable temperature deviation + 5°C; Conditions for closing balancing:

1. SOC difference < 5%; 2. The change value of the balancing difference within 1 hour is less than 1%; 3. The temperature difference between modules > the system allowable temperature deviation + 10°C; The specific algorithm for determining the open circuit voltage OCV and SOC of the battery pack in step 5 is as follows: read the cell freeze frame information of the battery pack, extract the absolute time of the most recent power-off moment of the battery pack, the SOC value, and the number of completed charge and discharge cycles; if the number of charge and discharge cycles N Chg The number is less than the threshold Th Chg , and the standing time t idl >OCV static judgment threshold Th idl , with the battery pack open circuit voltage V_ OCV As the battery voltage V Bat , SOC is obtained through the OCV-SOC function relationship f1(SOV,OCB); if the rest time is less than the OCV rest time threshold, the SOC recorded in the most recent power-off state is used as the initial charging SOC, and the real-time SOC estimation is performed based on the ampere-hour integration method, while the voltage at the later stage of constant current charging is used as a judgment.

2. The intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange according to claim 1, characterized in that: The Cloud brain adopts different charging balancing strategies for battery packs to be charged with different health levels. Specifically, the charging balancing device collects freeze frame information of the battery pack to be charged and uploads it to the ZUCC-IOT cloud; the ZUCC-IOT cloud communicates with the driving vehicle and obtains driving vehicle fault information; the Cloud brain evaluates the battery operation life cycle health information sent by the ZUCC-IOT cloud, communicates with the host terminal, and selects the most matching charging and balancing strategy and sends it to the ZUCC-IOT cloud.

3. The intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange as claimed in claim 1, characterized in that: The charging equalization device is composed of a PWM generator, a resonant converter and a voltage multiplier. The charging equalization device is used to achieve the equalization of the cells in the battery module or the cells after parallel connection. The charging equalization device is used to achieve the equalization within the module or between modules; the battery pack to be charged is provided with three connector interfaces, namely a standard charging interface, a fast charging interface and a equalization interface, and each interface is designed with a mechanical self-locking structure.

4. The intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange according to claim 1, characterized in that: The judgment basis of step 2 is the uniqueness of the binding between the battery to be charged and the identity of the vehicle it drives.

5. The intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange as claimed in claim 1, characterized in that: The basic information of the freeze frame in step 3 includes the unique code of the battery pack ID, the number of completed charge and discharge cycles, the operating time, the high-rate discharge time, the maximum discharge current, the historical highest temperature, the historical lowest temperature, the historical highest voltage, the historical lowest voltage, the battery SOC value stored at the last power outage, and the absolute time of the power outage; the protocols of ZUCC-IOT protocol-D and ZUCC-IOT protocol-U in step 3 are one of MQTTS or HTTPS, the data is encrypted using SSL or TLS, and the data is packaged and transmitted in one of GPB format, JSON format or XML format.

6. The intelligent charging equalization method of the intelligent charging equalization system based on cloud data exchange according to claim 1, characterized in that: The charging action in step 4 is carried out in four stages: pre-charging 1, pre-charging 2, constant current charging, and constant voltage charging. Battery balancing is automatically turned on in the late second stage of charging or in the third stage, and the user can decide to turn on or off balancing.

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