A control method and system for heavy truck battery replacement

Abstract

The application provides a control method and system for heavy truck battery replacement. The control method comprises: collecting health state parameters of a battery pack in real time; determining a health level of the battery pack based on the health state parameters through a preset health score model; when the coding information of a heavy truck battery replacement vehicle is detected, determining an adaptive software version range according to the adaptive relationship between the health level of the battery pack and the software version stored in a pre-created version matching library, and checking whether the software version to be written is within the adaptive software version range, if yes, selecting the software version to be written as the heavy truck battery replacement adaptive software version, and if no, selecting a compatible software version as the heavy truck battery replacement adaptive software version; and performing the writing of the heavy truck battery replacement adaptive software version according to a preset writing priority. According to the scheme of the application, the writing frequency can be reduced, the hardware loss can be reduced, and the operation efficiency of the battery replacement station can be improved.

Description

Technical Field

[0001] This invention relates to the field of battery swapping station technology, and more specifically, to a control method and system for battery swapping of heavy-duty trucks. Background Technology

[0002] In the field of heavy-duty truck battery swapping, due to the characteristics of large battery capacity, high usage intensity, and significant differences in health status, there are high requirements for software flashing of battery swapping packs. However, existing technical solutions do not take into account various factors such as battery health status and vehicle operating conditions. For example, patent CN113968163B only uses the battery swapping vehicle coding information to match the target version of the software to achieve flashing, without associating the health status parameters of the heavy-duty truck battery swapping pack. Heavy-duty truck battery packs experience significant variations in State of Health (SOH) degradation due to frequent high-load charging and discharging (e.g., daily mileage of 300-500km, with an annual cycle count increase of 200-300). For instance, some retired battery packs (SOH < 60%) are only used in low-speed heavy-duty trucks, and their hardware performance can no longer support the core functions of higher-version software. For example, functions such as fast charging in higher-version software may not be enabled on retired battery packs due to insufficient cell activity and reduced heat dissipation, which in turn increases the time required for the flashing process. During peak hours at heavy-duty truck battery swapping stations, such invalid flashing will consume more station control system resources, leading to longer waiting times for vehicles that are normally swapping batteries.

[0003] Furthermore, current technology employs a uniform strategy of forcibly flashing the latest version to all heavy-duty truck battery packs, without considering the tolerance of varying battery pack health conditions to flashing frequency. This is because the BMS (Battery Management System) chip in a new heavy-duty truck battery pack (SOH≥90%, cycle count<50) has a write lifespan of approximately 1000 cycles. If flashed 3 times per month using current technology, it would reach its write lifespan limit in just 5 years. While older battery packs (SOH 60%-80%, cycle count 200-500) have a larger BMS chip reserve, frequent flashing causes repeated activation of the cell balancing algorithm, accelerating cell consistency degradation.

[0004] Finally, existing technologies do not consider the relationship between the software functions of heavy-duty truck battery packs and vehicle operating conditions. For example, flashing a high-version software onto a retired battery pack (such as one requiring only basic discharge protection) can cause the battery pack to frequently trigger false alarms during short-distance, high-frequency start-stop operations, affecting operational efficiency. Conversely, flashing a low-version software (such as one without heavy-load overheat protection) onto a healthy trunk heavy-duty truck battery pack can cause the battery pack to overheat during uphill driving due to missing software functions, posing a safety hazard.

[0005] Based on the problems existing in the current technology, there is an urgent need to propose a solution that is suitable for heavy-duty trucks under high load and multiple operating conditions, to achieve accurate adaptation between the health status of the battery pack and the software version, optimize the flashing strategy, extend the life of the battery management system (BMS), and improve the operating efficiency of the battery swapping station. Summary of the Invention

[0006] Based on the technical problems described above, this invention aims to solve the problems in existing heavy-duty truck battery swapping technology where software flashing is not linked to battery health status and vehicle operating conditions, resulting in numerous invalid flashes, significant hardware wear, low operating efficiency of swapping stations, and potential safety hazards. The invention achieves precise matching between the battery pack health status and software version, optimizes the flashing strategy, extends the lifespan of the battery management system (BMS), reduces invalid flashes and hardware wear, improves the operating efficiency of swapping stations, and ensures the safety and reliability of heavy-duty truck battery swapping under different operating conditions.

[0007] Specifically, according to one aspect of the present invention, a control method for battery swapping of heavy-duty trucks is provided, the control method comprising:

[0008] Real-time collection of health status parameters of the battery pack;

[0009] Based on the health status parameters, the health level of the battery pack is determined by a preset health scoring model;

[0010] When the coding information of the heavy-duty truck battery swapping vehicle is detected, the range of compatible software versions is determined according to the compatibility relationship between the health level of the battery swapping battery pack and the software version stored in the pre-created version matching library. It is also verified whether the software version to be flashed is within the range of compatible software versions. If so, the software version to be flashed is selected as the compatible software version for heavy-duty truck battery swapping. If not, a compatible software version is selected as the compatible software version for heavy-duty truck battery swapping.

[0011] The flashing of the heavy-duty truck battery swapping adaptation software version is performed according to the preset flashing priority.

[0012] According to certain preferred embodiments of the present invention, the health status parameters include at least one of the following: state of health (SOH) index, number of cycles, cell voltage difference, and service life.

[0013] According to certain preferred embodiments of the present invention, the SOH index is calculated through a dual-model correlation of the capacity decay method and the impedance method, specifically including:

[0014] Based on the factory rated capacity of the battery pack and the corrected current remaining usable capacity, the capacity decay method SOH is calculated.

[0015] Based on the current total impedance, factory reference total impedance, and end-of-life total impedance of the battery pack, the impedance method SOH is calculated.

[0016] Based on the scenario in which the battery pack is located, weights are assigned to the SOH calculated by the capacity decay method and the SOH calculated by the impedance method, and the final SOH index is obtained by weighted calculation.

[0017] According to certain preferred embodiments of the present invention, the scenarios include static scenarios, dynamic scenarios, and extreme scenarios; in the static scenario, the weight of the capacity decay method SOH is greater than the weight of the impedance method SOH; in the dynamic scenario or the extreme scenario, the weight of the impedance method SOH is greater than the weight of the capacity decay method SOH.

[0018] According to certain preferred embodiments of the present invention, the health scoring model calculates a total health score by assigning weights to various health status parameters and quantifying them, and classifies health levels based on the total health score, including healthy battery, sub-healthy battery, and retired battery.

[0019] According to certain preferred embodiments of the present invention, the version matching library defines the range of compatible software versions and core functional modules corresponding to different health levels.

[0020] According to certain preferred embodiments of the present invention, the setting of the writing priority is based on the scenario type of the heavy-duty truck battery swapping vehicle and the health level of the battery swapping pack; wherein, under the same scenario type, the writing priority of healthy batteries is higher than that of sub-healthy batteries, and the writing priority of sub-healthy batteries is higher than that of retired batteries.

[0021] According to certain preferred embodiments of the present invention, the setting of the flashing priority further includes dynamic adjustment based on the emergency indicator in the battery swapping request, including: increasing the flashing priority by 2 levels in high urgency scenarios, increasing the flashing priority by 1 level in medium urgency scenarios, and not adjusting the flashing priority in low urgency scenarios.

[0022] According to certain preferred embodiments of the present invention, the control method further includes: setting different write frequency limits based on the health level of the battery pack.

[0023] According to certain preferred embodiments of the present invention, during the flashing process, a flashing queue is constructed according to the flashing priority, and different hardware resources are allocated to battery queues with different health levels; wherein, the proportion of hardware resources allocated to the healthy battery queue is higher than the proportion of hardware resources allocated to the retired battery queue.

[0024] According to another aspect of the present invention, a control system for battery swapping of heavy-duty trucks is provided, comprising:

[0025] The battery swapping controller is used to collect the coding information of heavy-duty truck battery swapping vehicles and the health status parameters of the battery swapping pack in real time.

[0026] The battery swapping station cloud platform is used to store a version matching library and determine the appropriate software version based on the received coding information of the heavy-duty truck battery swapping vehicle and the health level of the battery swapping pack.

[0027] The battery swapping station control system is used to determine the health level of the battery swapping pack based on the health status parameters through a health scoring model, and to receive the adapted software version issued by the battery swapping station cloud platform and perform flashing according to the flashing priority.

[0028] The battery pack is used to communicate with the station control system of the battery swapping station, and to receive and run the flashed software version.

[0029] According to certain preferred embodiments of the present invention, the battery swapping controller collects the health status parameters via a CAN bus and performs filtering processing on the collected parameters.

[0030] According to certain preferred embodiments of the present invention, the battery swapping station cloud platform includes:

[0031] The data storage unit is used to store the version matching library, the heavy truck-standard version mapping table, and the write logs.

[0032] The adaptation verification unit is used to verify and determine the compatible software version based on the heavy-duty truck battery swapping vehicle coding information and the health level.

[0033] The dynamic update unit is used to update the adaptation rules in the version matching library based on the flashing results and operating condition data.

[0034] The information sending unit is used to send the battery swapping completion status information to the user terminal.

[0035] According to certain preferred embodiments of the present invention, the heavy truck vehicle-standard version mapping table is associated with the initial software version to be flashed based on the vehicle code suffix; wherein, the code containing the suffix "TK" is associated with version V3.0 and above, the code containing the suffix "CJ" is associated with versions V2.0 to V2.5, and the code containing the suffix "GK" is associated with version V1.5.

[0036] According to certain preferred embodiments of the present invention, the station control system of the battery swapping station includes:

[0037] The software receiving unit is used to receive the adapted software version issued by the battery swapping station cloud platform;

[0038] A battery health assessment unit is used to determine the health level using the health scoring model;

[0039] A software flashing unit is used to perform software flashing according to the flashing priority;

[0040] The information feedback unit is used to send the writing status information back to the battery swapping station cloud platform.

[0041] According to certain preferred embodiments of the present invention, the battery swapping pack includes a battery pack and a battery management system (BMS) module, wherein the BMS module supports State of Health (SOH) calculation and communicates with the battery swapping controller via a CAN bus.

[0042] According to certain preferred embodiments of the present invention, when the system performs flashing, it allocates different hardware resources to battery queues with different health levels, and automatically shuts down the flashing of retired battery queues during peak periods.

[0043] According to another aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described control method for heavy-duty truck battery swapping.

[0044] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described control method for heavy-duty truck battery swapping.

[0045] By adopting the method and system of this invention, the health status of the battery pack and the software version can be more accurately matched, reducing invalid writes, extending the BMS of heavy truck batteries, reducing hardware wear and tear, and improving the operational efficiency of battery swapping stations. Attached Figure Description

[0046] The accompanying drawings are provided in this specification to more clearly explain the technical solutions of the present invention; however, the art is not limited thereto.

[0047] Figure 1 A flowchart of the control method for battery swapping of heavy-duty trucks according to the present invention is shown;

[0048] Figure 2 A block diagram of a heavy-duty truck battery swapping control system according to an embodiment of the present invention is shown;

[0049] Figure 3 This diagram shows a structural block diagram of a battery swapping station cloud platform according to an embodiment of the present invention.

[0050] Figure 4 A block diagram of a battery swapping station control system according to an embodiment of the present invention is shown.

[0051] Explanation of reference numerals in the attached figures:

[0052] S1-S4 are the process steps of the control method; 10 Battery swapping controller; 20 Battery swapping station cloud platform; 30 Battery swapping station control system; 40 User terminal; 50 Battery swapping battery pack; 201 Data storage unit; 202 Adaptation verification unit; 203 Dynamic update unit; 204 Information sending unit; 301 Software receiving unit; 302 Battery health assessment unit; 303 Software flashing unit; 304 Information feedback unit. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0055] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0056] Example 1

[0057] like Figure 1 As shown, the control method for battery swapping of heavy trucks provided in this embodiment of the invention includes steps S1-S4.

[0058] In step S1, the health status parameters of the battery pack are collected in real time. These parameters are acquired via a dedicated CAN bus for heavy-duty trucks. The health status parameters include at least the State of Health (SOH) index, cycle count, cell voltage difference, and service life. The determination scheme for each index is detailed below.

[0059] 1. SOH index: It can be calculated by using the capacity decay method and impedance method dual model correlation. In order to adapt to the sudden change in health status of heavy trucks under short-term high load conditions, the sampling frequency can be set to 1 time / 30s.

[0060] Among them, since heavy-duty truck battery packs generally have relatively large capacities, such as ≥200kWh, and more cycle times compared to battery packs of other types of vehicles, for example, the number of cycle times increases by 200-300 times per year, capacity decay is the core parameter of the health status of heavy-duty truck battery packs.

[0061] 1. The calculation method based on the capacity decay method is as follows:

[0062] First, the factory rated capacity of the heavy-duty truck battery pack is collected from the factory parameters stored in the battery pack BMS, for example, 200kWh; and the current actual usable capacity of the heavy-duty truck battery pack is collected, and the "complete charge and discharge cycle" data is recorded by the charger of the battery swapping station (for example, after the heavy-duty truck is swapped, it is fully charged to the cutoff voltage of 4.2V / cell and discharged to the cutoff voltage of 2.5V / cell), and the discharge capacity is calculated.

[0063] Secondly, the discharge capacity is corrected according to the influence of the environment and discharge rate of heavy truck discharge, that is:

[0064] The environmental impact during the charging and discharging of heavy-duty trucks is corrected. For example, in summer when the temperature is high (>35℃), the actual capacity is corrected by 1.02 times; in winter when the temperature is low (<0℃), the actual capacity is corrected by 0.95 times.

[0065] To correct for the impact of charge / discharge rate, the actual capacity of heavy-duty trucks is corrected by 0.98 times when subjected to high-current discharge (>1C).

[0066] The corrected value is the current remaining available capacity of the heavy truck's battery pack, for example, 118 kWh.

[0067] Finally, calculate SOH using the following formula:

[0068] SOH = (Current remaining available capacity / Factory rated capacity) × 100%;

[0069] Taking the heavy-duty truck battery pack mentioned above as an example, its corrected remaining usable capacity is 118kWh, and its factory rated capacity is 200kWh. Therefore, according to the formula, the SOH of the battery pack is (118 / 200)×100%=59%.

[0070] 2. On the other hand, considering the special characteristics of the heavy-duty truck industry, when a heavy-duty truck discharges at a high current (such as >200A when climbing a hill), it will cause a sharp increase in impedance. This impedance change can quickly reflect the battery's health degradation. Since SOH (State of Harmony) is negatively correlated with battery impedance, meaning the higher the impedance, the lower the SOH, the calculation method based on impedance is as follows:

[0071] First, the impedance parameters of the battery pack for heavy-duty trucks are collected. The ohmic impedance (R1, reflecting the resistance of the electrodes and electrolyte) and polarization impedance (R2, reflecting the resistance of the electrochemical reaction) of the battery pack are detected in real time. The sampling frequency can be set to once every 30 seconds to adapt to the impedance changes caused by short-term heavy loads on heavy-duty trucks.

[0072] Secondly, establish the impedance reference, i.e., the factory reference impedance: store the R1 (e.g., 0.01Ω) and R2 (e.g., 0.03Ω) of the battery pack at the factory; further, obtain the attenuation impedance curve: based on the heavy truck battery pack life test data, establish "impedance growth - SOH attenuation" to obtain the corresponding curve, such as R1 increasing by 50% corresponding to SOH attenuation of 20%.

[0073] Finally, the SOH index is calculated as follows:

[0074] SOH = 100% - [(Current Total Impedance - Factory Reference Total Impedance) / (End-of-Life Total Impedance - Factory Reference Total Impedance)] × 100%;

[0075] Wherein, total impedance = R1 + R2;

[0076] Taking the aforementioned heavy-duty truck battery pack as an example, the current R1=0.015Ω and R2=0.045Ω (total impedance R1+R2=0.06Ω). The factory-specified total impedance is 0.04Ω, and the end-of-life total impedance is 0.1Ω. Therefore, SOH=100%- [(0.06-0.04) / (0.1-0.04)]×100%≈66.7%.

[0077] 3. Correlation calculation using both capacity attenuation method and impedance method

[0078] The final SOH index is obtained by using a weighted algorithm combining the capacity decay method and the impedance method, which is more suitable for heavy-duty truck operation scenarios. Specifically:

[0079] First, assign weights: In static scenarios, such as port heavy trucks idling and waiting for battery swapping, the weight of the capacity decay method is set to 60%, and the weight of the impedance method is set to 40%. In dynamic scenarios, such as long-haul heavy trucks temporarily swapping batteries while driving, the weight of the capacity decay method is set to 40%, and the weight of the impedance method is set to 60%, because the impedance of a vehicle in dynamic conditions can quickly reflect sudden changes in health. In extreme scenarios, such as when the battery pack has just been overcharged or over-discharged, the weight of the impedance method is set to 80%, and the weight of the capacity decay method is set to 20%, because impedance changes are more sensitive after overcharging or over-discharging.

[0080] Secondly, the correlation calculation is performed according to the following calculation method:

[0081] The final SOH = (SOH by capacity decay method × capacity weight) + (SOH by impedance method × impedance weight).

[0082] Taking the aforementioned heavy-duty truck battery pack as an example, in a static port scenario, the SOH of the capacity decay method is 59% (weighted at 60%), and the SOH of the impedance method is 66.7% (weighted at 40%). Therefore, the final SOH is 59%×60%+66.7%×40%≈62.18%, which can be corrected to approximately 62% with an accuracy of ±1%.

[0083] Finally, the results are verified: if the difference in SOH calculated by the two methods is greater than 5%, a "re-detection" is triggered, such as re-executing a charge-discharge cycle or re-collecting impedance data; if the difference is less than or equal to 5%, the final SOH is output and stored in the battery swapping station cloud platform.

[0084] II. Number of cycles collected: The number of cycles is obtained by combining the battery swapping records of heavy truck swapping stations and the statistics of battery pack BMS logs;

[0085] 3. Collect cell voltage difference: Monitor the voltage difference of all cells in real time. In order to avoid the problem of local overheating caused by exceeding the tolerance under the high current discharge of heavy trucks, the collection frequency can be set to 1 time / 10s, and the threshold can be set to ≤50mV.

[0086] IV. Data Collection Service Duration: The data is automatically updated daily at midnight, starting from the manufacturing date of the heavy-duty truck battery pack. This parameter allows us to focus on battery packs with longer service lives, as these packs are entering a period of rapid degradation.

[0087] In step S2, based on the health status parameters, the health level of the battery pack is determined using a preset health scoring model. The specific scheme is as follows:

[0088] Table 1: Health Scoring Model

[0089]

[0090] In step S3, when the coding information of the heavy-duty truck battery swapping vehicle is detected, the range of compatible software versions is determined based on the compatibility relationship between the health level of the battery pack and the software version stored in the pre-created version matching library. It is then verified whether the software version to be flashed is within the range of compatible software versions. If so, the software version to be flashed is selected as the compatible software version for the heavy-duty truck battery swapping; otherwise, a compatible software version is selected. Specifically, the following scheme is adopted:

[0091] The system retrieves the coding information of the heavy-duty truck battery swapping vehicle and the corresponding software version information from the battery swapping station cloud platform. For example, if the heavy-duty truck battery swapping vehicle coding information is "TK-2024001", and its corresponding software version is V3.0 based on its health level, it verifies whether this software version is within the range of compatible software versions in the version matching library in Table 2. For example, if the battery pack is a healthy battery and the version to be flashed is V3.0, and the version matching library in Table 3 shows that this type of battery can be used with V3.0 and above, then the software version V3.0 is selected as the compatible software version for the heavy-duty truck battery swapping to be flashed, which means the verification is successful. If the verification fails, for example, if the current software version corresponding to a certain type of battery is V3.0, but according to its health level and version matching library, the version to be flashed for this type of battery should be within the range of V1.5, then the compatible software version that matches the current health level, i.e., V1.5, is retrieved and sent to the battery swapping station control system as the compatible software version for the heavy-duty truck battery swapping to be flashed.

[0092] Table 2: Version Matching Library

[0093]

[0094] In step S4, the heavy-duty truck battery swapping adaptation software version is flashed according to a pre-set flashing priority. Factors considered when prioritizing the flashing priority include: the type of heavy-duty truck battery swapping scenario, battery health level, dynamic adjustment for emergency scheduling, and flashing frequency. Specifically, the following scheme is adopted:

[0095] 1) The priority for performing the flashing operation is set based on the type of heavy-duty truck battery swapping scenario and the battery's health level (level 1 is the highest, level 10 is the lowest), as shown in Table 3 below:

[0096] Table 3: Initial settings for flash priority

[0097]

[0098] 2) Set dynamic adjustment rules for urgency. The battery swapping station control system can read the "emergency flag" in the heavy truck battery swapping request and adjust the priority according to the current dispatch situation. For example: In high-urgency scenarios, such as battery alarms during driving requiring emergency battery swapping to restore operation; heavy trucks transporting hazardous materials at ports requiring rapid battery swapping; and intercity heavy trucks transporting fresh produce in cold chain logistics requiring fast delivery, the priority of this data swipe is increased by 2 levels. In medium-urgency scenarios, such as ordinary trunk line heavy trucks during daytime peak transportation hours with battery swapping waiting time > 30 minutes; and heavy trucks transporting fresh produce at ports requiring delivery time ≤ 8 hours, the priority of this data swipe is increased by 1 level. In low-urgency scenarios, such as ordinary port heavy trucks during off-peak hours at night, and intercity empty heavy trucks without clear delivery time requirements, the priority of this data swipe is not adjusted.

[0099] 3) Set frequency limit rules and set the number of times to limit the flashing frequency according to the battery health level.

[0100] 4) During the flashing process, the battery swapping station control system constructs flashing queues from high to low priority, with queues of the same priority ordered by the time of the battery swapping request. The retired battery queue is physically isolated from the healthy and sub-healthy battery queues to avoid consuming core resources. Regarding resource allocation, the battery swapping station allocates only 10% of its hardware resources (such as charger interfaces and CAN bus bandwidth) to the retired battery queue, 50% to the healthy battery queue, and 40% to the sub-healthy battery queue. During peak hours, the retired battery queue is automatically shut down, only remaining open at night. Following these priority scheduling rules, the battery swapping station control system sends flashing commands to the battery packs, completes the flashing process, and uploads the flashing status to the battery swapping station cloud platform.

[0101] By adopting the heavy-duty truck battery swapping control method of the present invention, it can be deeply integrated with the application scenarios of heavy-duty trucks. Based on comprehensive indicators such as battery health level, battery swapping urgency, flashing priority and flashing frequency, it can achieve precise adaptation between the battery pack health status and software version, optimize the flashing strategy, reduce invalid flashing, reduce hardware wear and tear and improve the operating efficiency of battery swapping stations.

[0102] Example 2

[0103] like Figure 2 As shown, the specific scheme of the control system corresponding to the above-mentioned heavy truck battery swapping control method is as follows: The control system includes:

[0104] 1. A battery swapping controller 10 is used to collect data such as the coding information of the heavy-duty truck battery swapping vehicle, the health status parameters of the battery swapping pack 50, and the current software version in real time, and send the information to the battery swapping station cloud platform 20. Specifically, the battery swapping controller 10 collects the coding information of the heavy-duty truck battery swapping vehicle, battery swapping scenario information, health status parameters of the battery swapping pack 50 (such as SOH, cycle count, etc.), and the current software version information of the battery pack through the CAN bus; the battery swapping controller 10 performs filtering processing on the collected health status parameters, such as removing instantaneous abnormal voltage peaks, to ensure the accuracy of the data; then, the battery swapping controller 10 sends the processed information to the battery swapping station cloud platform 20 at a certain frequency period.

[0105] 2. The battery swapping station cloud platform 20 stores a version matching library. When the coding information of a heavy-duty truck battery swapping vehicle is detected, it verifies the compatibility based on the initial version to be flashed for the battery swapping vehicle and the health level of the battery pack 50, and then sends the appropriate software version to the battery swapping station control system 30. For example... Figure 3As shown, the structure of the battery swapping station cloud platform 20 of the present invention includes: a data storage unit 201, an adaptation verification unit 202, a dynamic update unit 203, and an information feedback unit 304, specifically:

[0106] 1) Data storage unit 201: Stores "version matching library", "heavy truck vehicle-standard version mapping table", and write log, which includes health level, software version, write result, user terminal 40 information, etc.

[0107] Table 4: Mapping Table of Heavy-Duty Trucks - Standard Versions

[0108]

[0109] 2) Adaptation verification unit 202: When the heavy truck battery swapping vehicle coding information is detected, the adaptation verification unit 202 verifies the compatibility of the version to be flashed based on the initial version to be flashed determined in Table 4 above, and sends out the adapted software version.

[0110] 3) Dynamic update unit 203: Real-time analysis of related data such as battery health level, software version and flashing results; for example: if the failure rate of a certain version in a certain health level battery is >5% (such as the cell error rate increases after flashing version V2.3 of a sub-healthy battery), then the version will be removed from the adaptation range; the adaptation rules will be updated quarterly according to changes in heavy truck operating conditions (such as high temperatures in summer).

[0111] 4) Information sending unit 204: Receives the writing status information uploaded by the battery swapping station control system 30, generates battery swapping completion status information, which includes the battery swapping station address, battery health level, compatibility conditions, etc., and sends it to the heavy truck user terminal 40, such as the vehicle system or mobile APP, through the 4G / 5G network.

[0112] 3. The battery swapping station control system 30 is used to set the health scoring model of the battery swapping pack 50 to determine the health level of the battery swapping pack 50, and to receive the software version to be flashed sent by the battery swapping station cloud platform 20, and to perform software flashing according to the flashing priority.

[0113] like Figure 4 As shown, the battery swapping station control system 30 of the present invention includes:

[0114] 1) Software receiving unit 301 is used to receive the heavy truck battery swapping adaptation software version sent by the battery swapping station cloud platform 20;

[0115] 2) Battery health assessment unit 302, used to quantify the health status parameters and set the health level using a health scoring model;

[0116] 3) Software flashing unit 303 is used to pre-set the flashing priority and to flash the heavy truck battery swapping adaptation software version into the battery swapping battery pack 50.

[0117] 4) Information feedback unit 304: used to feed back the writing status information to the battery swapping station cloud platform 20.

[0118] 4. The battery swapping pack 50 is used to communicate with the station control system 30 of the battery swapping station, receive and run the flashed heavy-duty truck battery swapping adaptation software version, and enable the corresponding functions of the battery pack. Specifically, the battery swapping pack 50 includes a heavy-duty truck battery pack and a BMS module, which supports SOH calculation and a CAN communication interface. The battery swapping pack 50 sends the battery pack's health status parameters and current software version information to the battery swapping controller 10 via the CAN bus; the battery swapping pack 50 receives the heavy-duty truck battery swapping adaptation software version issued by the station control system 30 and stores it in the BMS chip; the battery swapping pack 50 runs the flashed software version and enables the corresponding functions.

[0119] By adopting the three-level collaborative system structure of the battery swapping controller, the battery swapping station cloud platform, and the battery swapping station control system of this invention, functional modular division of labor is achieved. Among them, the battery swapping controller focuses on the collection and preprocessing of heavy-duty truck-specific health parameters to ensure the accuracy and real-time performance of raw data collection; the battery swapping station cloud platform focuses on data storage and version adaptation decisions; and the battery swapping station control system is responsible for determining the health level and scheduling the priority of data writing. The control system for heavy-duty truck battery swapping using this invention can effectively control the resource occupancy rate of each structure and prevent data writing interruptions.

[0120] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a processor-included system or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).

[0121] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0122] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0123] It should also be further understood that the term "and / or" as used in this specification refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes such combinations.

[0124] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A control method for battery swapping in heavy-duty trucks, characterized in that, The control method includes: S1, real-time collection of health status parameters of the battery pack; S2, based on the health status parameters, the health level of the battery pack is determined by a preset health scoring model. The health status parameters include at least one of the following: health status SOH index, number of cycles, cell voltage difference, and service life. The health scoring model calculates the total health score by assigning weights to each health status parameter and performing quantitative scoring. Based on the total health score, the health levels are divided into healthy batteries, sub-healthy batteries, and retired batteries. S3. When the coding information of the heavy-duty truck battery swapping vehicle is detected, the range of compatible software versions is determined according to the compatibility relationship between the health level of the battery swapping battery pack and the software version stored in the pre-created version matching library. The software version to be flashed is verified to be within the range of compatible software versions. If so, the software version to be flashed is selected as the compatible software version for heavy-duty truck battery swapping. If not, a compatible software version is selected as the compatible software version for heavy-duty truck battery swapping. S4. According to the preset flashing priority, the flashing of the heavy truck battery swapping adaptation software version is performed.

2. The control method according to claim 1, characterized in that, The SOH index is calculated using a dual-model correlation of the capacity decay method and the impedance method, specifically including: Based on the factory rated capacity of the battery pack and the corrected current remaining usable capacity, the capacity decay method SOH is calculated. Based on the current total impedance, factory reference total impedance, and end-of-life total impedance of the battery pack, the impedance method SOH is calculated. Based on the scenario in which the battery pack is located, weights are assigned to the SOH calculated by the capacity decay method and the SOH calculated by the impedance method, and the final SOH index is obtained by weighted calculation.

3. The control method according to claim 1, characterized in that, The version matching library defines the range of compatible software versions and core functional modules corresponding to different health levels.

4. The control method according to claim 1, characterized in that, The flashing priority is set based on the scenario type of the heavy-duty truck battery swapping vehicle and the health level of the battery swapping pack; wherein, under the same scenario type, the flashing priority of healthy batteries is higher than that of sub-healthy batteries, and the flashing priority of sub-healthy batteries is higher than that of retired batteries.

5. The control method according to claim 1, characterized in that, During the flashing process, a flashing queue is constructed based on the flashing priority, and different hardware resources are allocated to battery queues with different health levels; among them, the proportion of hardware resources allocated to the healthy battery queue is higher than the proportion of hardware resources allocated to the retired battery queue.

6. A control system for battery swapping in heavy-duty trucks, characterized in that, include: The battery swapping controller is used to collect the coding information of heavy-duty truck battery swapping vehicles and the health status parameters of the battery swapping pack in real time. The battery swapping station cloud platform is used to store a version matching library and determine the appropriate software version based on the received coding information of the heavy-duty truck battery swapping vehicle and the health level of the battery swapping pack. The battery swapping station control system is used to determine the health level of the battery swapping pack based on the health status parameters through a health scoring model, and to receive the adapted software version issued by the battery swapping station cloud platform and perform flashing according to the flashing priority. The battery pack for battery swapping is used to communicate with the station control system of the battery swapping station, receive and run the flashed software version, wherein... The health status parameters include at least one of the following: State of Health (SOH) index, number of cycles, cell voltage difference, and service life. The health scoring model calculates a total health score by assigning weights to each health status parameter and quantifying the score. Based on the total health score, the model classifies the health levels into healthy batteries, sub-healthy batteries, and retired batteries.

7. The control system according to claim 6, characterized in that, The battery swapping station cloud platform includes: The data storage unit is used to store the version matching library, the heavy truck-standard version mapping table, and the write logs. The adaptation verification unit is used to verify and determine the compatible software version based on the heavy-duty truck battery swapping vehicle coding information and the health level. The dynamic update unit is used to update the adaptation rules in the version matching library based on the flashing results and operating condition data. The information sending unit is used to send the battery swapping completion status information to the user terminal.

8. The control system according to claim 6, characterized in that, The station control system of the battery swapping station includes: The software receiving unit is used to receive the adapted software version issued by the battery swapping station cloud platform; A battery health assessment unit is used to determine the health level using the health scoring model; A software flashing unit is used to perform software flashing according to the flashing priority; The information feedback unit is used to send the writing status information back to the battery swapping station cloud platform.

Images