Intelligent excavator upgrading method

Abstract

The invention provides an intelligent excavator upgrading method, which belongs to the field of excavator intellectualization, and comprises the following steps that: a user downloads an upgrading package required by a target excavator to a local application program, and after the local application program establishes connection with a vehicle end system of the target excavator and completes authentication, an upgrading instruction is sent to a man-machine interaction system in the vehicle end system; after the man-machine interaction system receives the upgrading instruction, the priorities of all the available signal sources are obtained, and stability judgment is conducted on all the signal sources; selecting the signal source with the highest priority from the stable signal sources as a downloading channel, and downloading upgrade package data from a local application program; and after verification is completed, transmitting the upgrade package data to the target element, and executing a conventional upgrade process. Upgrading of all elements is managed in a centralized mode through the man-machine interaction system, professional equipment is not needed, automatic preferential downloading of multiple signal sources can be achieved, stability of the signal sources is dynamically monitored, stability and reliability of upgrading are guaranteed, and the success rate of flashing is increased.

Description

Technical Field

[0001] This invention relates to a method for intelligent upgrading of excavators, belonging to the field of excavator intelligence. Background Technology

[0002] With the development of intelligent and connected technologies, excavators have increasingly higher demands for intelligent control, resulting in a growing number of ECUs installed on a single excavator. The software versions of these ECUs directly determine the overall performance, efficiency, and safety of the machine. Continuous software updates have become a core means of enhancing the value of excavators, fixing potential vulnerabilities, and adapting to new functions and operating conditions.

[0003] Traditional excavator component upgrades have the following drawbacks:

[0004] (1) It relies on specialized equipment, requires on-site upgrades by service personnel, and is complex, costly and inefficient.

[0005] (2) The ECUs on the excavators come from different suppliers, and their software upgrade tools and processes are different. There is a lack of a unified central node to coordinate and manage the entire upgrade process, which makes the upgrade process complicated and the upgrade status cannot be centrally controlled.

[0006] (3) Some existing vehicle systems receive upgrade packages remotely through vehicle terminals in a 4G / 5G network environment, but excavators are often in remote areas with poor network signals, resulting in poor upgrade stability and low upgrade success rate; some vehicle systems transmit upgrade packages to the vehicle via Bluetooth communication, but only support a single channel, which inevitably leads to long processing time and instability when transmitting large files.

[0007] Therefore, excavators urgently need an efficient, reliable, and flexible intelligent upgrade solution. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of the prior art and provide an intelligent upgrade method for excavators. By using a human-machine interaction system and multiple communication methods, the optimal upgrade source is intelligently selected, which solves the problems of poor stability and low success rate of excavator component upgrades.

[0009] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0010] This invention provides an intelligent upgrade method for excavators, comprising: a user downloading the upgrade package required by the target excavator to a local application; after the local application establishes a connection with the target excavator's vehicle-side system and completes authentication, sending the upgrade command to the human-machine interaction system in the vehicle-side system.

[0011] After receiving the upgrade command, the human-computer interaction system first obtains the priority of each available signal source and determines the stability of each signal source. Then, it selects the highest priority signal source from the stable signal sources as the download channel and downloads the upgrade package data from the local application. After completing the verification, the upgrade package data is transmitted to the target component, and the normal upgrade process is executed.

[0012] As an optional technical solution of the present invention, obtaining the priority of each available signal source includes: filtering the currently available download signal sources to obtain a set of candidate signal sources; collecting network quality data of each signal source in the set of candidate signal sources, and normalizing the network quality data;

[0013] The normalized network quality data is input into the weighted scoring model, and the comprehensive quality score of each candidate signal source is obtained by combining the weight coefficients of each network quality data. The priority of each candidate signal source is set according to the comprehensive quality score from high to low.

[0014] As an optional technical solution of the present invention, the network quality data includes: estimated bandwidth, network latency, network jitter, packet loss rate, and link cost.

[0015] As an optional technical solution of the present invention, the weight coefficients of each network quality data are dynamically allocated according to the size of the upgrade package. Specifically, if the upgrade package size is less than the first threshold, it is defined as a small package, and the weight configuration is biased towards network latency and network jitter; if the first threshold is less than or equal to the upgrade package size and less than the second threshold, it is defined as a medium package, and the weight configuration is biased towards estimated bandwidth, network latency, and cost; if the upgrade package size is greater than or equal to the second threshold, it is defined as a large package, and the weight configuration is biased towards estimated bandwidth and packet loss rate.

[0016] As an optional technical solution of the present invention, the weighted scoring model is as follows:

[0017]

[0018] In the formula, For the overall quality score, For normalization function, To estimate bandwidth, Due to network latency, For network jitter, For packet loss rate, For link cost, These are the weighting coefficients for estimated bandwidth, network latency, network jitter, packet loss rate, and link cost, respectively.

[0019] As an optional technical solution of the present invention, the stability determination of each signal source is specifically as follows: if the packet loss rate of the signal source is not greater than the third threshold and the network jitter is not greater than the fourth threshold, then the signal source is determined to be stable; otherwise, the signal source is determined to be unstable.

[0020] As an optional technical solution of the present invention, it further includes: continuously monitoring the predicted remaining time of the current download channel during the download process; if the predicted remaining time of the current download channel exceeds the predicted total download time of other candidate signal sources, or the network of the current download channel is disconnected, the current download channel is automatically paused and switched to the next priority signal source for relay download.

[0021] As an optional technical solution of the present invention, before transmitting the upgrade package data to the target component, the method further includes: obtaining the current vehicle operating condition information and determining whether the conditions for safe upgrade are met; and transmitting the upgrade package data to the target component through the communication network configured in the original vehicle only when the vehicle operating condition information meets the conditions for safe upgrade.

[0022] As an optional technical solution of the present invention, the human-machine interaction system includes: a communication unit, a main control computing unit, a vehicle data acquisition unit, and a memory; the communication unit integrates multiple communication modules; the main control computing unit runs the core program of the operating system and algorithm; the vehicle data acquisition unit acquires vehicle operating condition information through the CAN bus; and the memory is used to store downloaded upgrade packages and algorithm running data.

[0023] As an optional technical solution of the present invention, the communication unit integrates a WiFi module, a Bluetooth module, a 4G / 5G module and a USB interface.

[0024] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0025] (1) The excavator intelligent upgrade method provided by the present invention centrally manages the upgrade of all components through a human-machine interaction system, without the need for professional equipment, and can realize automatic selection and download of multiple signal sources, and dynamically monitor the stability of signal sources to ensure the stability and reliability of the upgrade and improve the success rate of writing.

[0026] (2) All key operations in the excavator intelligent upgrade method provided by the present invention are completed in close proximity, avoiding the security risks that may be caused by data transmission on the public network. The components on the vehicle can be upgraded anytime and anywhere, without relying on Internet connection and remote cloud platform, and are not affected by network signal. Attached Figure Description

[0027] Figure 1 This is a hardware system diagram of the excavator intelligent upgrade method provided in Embodiment 1 of the present invention;

[0028] Figure 2 This is a flowchart illustrating the intelligent upgrade method for excavators provided in Embodiment 1 of the present invention. Detailed Implementation

[0029] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. The technical solutions of the embodiments of this application will now be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0030] Example 1

[0031] This embodiment provides an intelligent upgrade method for excavators. By using a human-machine interaction system as an interactive terminal, the system intelligently and dynamically selects the best signal source to download the upgrade package, thereby upgrading the program of the on-board components and ensuring reliable upgrades can be completed under various harsh working conditions.

[0032] Figure 1 The diagram shows the hardware system on which this method depends, including: an application APP for triggering the upgrade task, a human-machine interaction system as an interactive terminal, and vehicle components such as ECU1, ECU2, and ECU3. The APP can be installed on a mobile phone or tablet. The human-machine interaction system is the core component of the hardware system and communicates with vehicle components via CAN bus, vehicle Ethernet, or WiFi.

[0033] In some embodiments, the human-machine interface system includes: a communication module group, a main control computing unit, a vehicle data acquisition unit, and a memory. The communication module group integrates multiple communication modules; the main control computing unit runs an operating system and is the core program of the algorithm; the vehicle data acquisition unit acquires key operating condition information such as engine status and battery voltage via the CAN bus; and the memory is used to store downloaded upgrade packages and algorithm running data.

[0034] In some specific embodiments, the communication module group integrates communication modules such as WiFi module, Bluetooth module, 4G / 5G module and USB interface.

[0035] The following is for reference. Figure 2 This section introduces methods for intelligent upgrades of excavators based on the above hardware systems, including:

[0036] First, the upgrade task is triggered. This method uses an APP to trigger the upgrade, as follows: The user logs in to their personal account in the APP, enters the serial number of the target excavator, and after authorization, allows the download of the upgrade package for the target excavator. The user should download the required upgrade package for the target excavator in advance in a good network environment and store it locally on the APP installation carrier.

[0037] Once the user arrives at the target excavator site, they open the APP. The APP connects to the target excavator's onboard system via Bluetooth or WiFi. After the connection is established, two-way authentication is completed.

[0038] The user selects the downloaded upgrade package file on the app interface and clicks "Transfer". The app then sends the upgrade command to the human-computer interaction system.

[0039] Next, signal source detection and availability screening are performed. After the human-computer interaction system receives the upgrade instruction from the APP, it first detects all currently available download signal sources, and then performs preliminary screening of the signal sources based on the physical connection status and user-preset strategies to obtain a set of candidate signal sources.

[0040] The following are some common signal sources:

[0041] The first option is a USB flash drive. USB flash drives require physical contact from the user. If a USB flash drive is not detected, it is excluded. If a USB flash drive is detected, it is kept as an "offline" option. The priority rule for USB flash drives is independent. If the upgrade package version on the USB flash drive is correct and usable, it is always recommended that the user upgrade using the USB flash drive first, because its speed and stability are physically determined.

[0042] The second option is Bluetooth. Bluetooth bandwidth is typically low, and transferring large files is time-consuming and unstable. Therefore, when the upgrade package exceeds the threshold of 1, the Bluetooth option should be disabled directly, unless other networks are completely unavailable.

[0043] The third type is 4G / 5G. To use 4G / 5G, you need to check the SIM card status first to determine if you are roaming. Also, since 4G / 5G may consume the user's limited data allowance and incur charges, you also need to check the user settings, such as whether the user allows the use of mobile data to download large files. If the user has set it to "Download via WiFi only", then this option should be excluded.

[0044] The fourth type is WiFi. To use WiFi, you need to check if you are connected to WiFi and obtain an IP address.

[0045] After obtaining the candidate signal source set, a multi-dimensional network quality evaluation is performed, which specifically includes: collecting network quality data for each signal source in the candidate signal source set, and normalizing the network quality data, mapping indicators of different dimensions to the [0,1] interval, where 1 represents the best.

[0046] Next, dynamic weight allocation and comprehensive score calculation are performed, including: inputting the normalized network quality data into the pre-built weighted scoring model, combining the dynamically allocated weight coefficients of each network quality data to obtain the comprehensive quality score of each candidate signal source; finally, setting the priority of each candidate signal source according to the comprehensive quality score from high to low.

[0047] In this embodiment, the candidate signal source with the highest overall quality score Q is selected as the preferred download channel; however, before downloading, the stability of the preferred download channel needs to be determined based on packet loss rate and network jitter.

[0048] In some specific embodiments, the stability determination is based on the following criteria: if the packet loss rate of the signal source is not greater than the third threshold and the network jitter is not greater than the fourth threshold, then the signal source is determined to be stable; otherwise, the signal source is determined to be unstable.

[0049] After obtaining the priority of each available signal source and determining the stability of each signal source, intelligent decision-making is made to select the highest priority signal source among the stable signal sources as the download channel to download the upgrade package data from the application APP.

[0050] During the download process, the human-computer interaction system continuously monitors the network quality data of the current download channel. If the performance degrades and the predicted remaining download time exceeds the predicted total download time of other candidate signal sources, or if the current network is disconnected, the current download will be automatically paused and the system will switch to the next priority signal source for relay download.

[0051] After the download is complete, a verification is performed. If the verification fails, the file is automatically deleted and the upgrade task is retried. If the verification passes, the human-computer interaction system identifies the target component based on the received upgrade package, determines the communication protocol, and parses the upgrade package into a communication protocol compatible with the component, such as UDS protocol, J1939 protocol, or a custom protocol.

[0052] After verification, the upgrade package data is transferred to the target component, and the regular upgrade process is executed.

[0053] In some specific embodiments, before transmitting the upgrade package data to the target component, the method further includes: obtaining current vehicle operating condition information and determining whether the conditions for a safe upgrade are met; and transmitting the upgrade package data to the target component only when the vehicle operating condition information meets the conditions for a safe upgrade, through the communication network configured in the original vehicle.

[0054] After the upgrade is complete, the human-computer interaction system will display "Upgrade successful" and generate an encrypted data packet containing upgrade logs such as user information, operation time, and upgrade version information, which will be sent back to the APP. At the same time, if the signal is good, it will be automatically sent back to the cloud.

[0055] Example 2

[0056] Based on Example 1, this example provides a weighted scoring model for evaluating network quality.

[0057] In this embodiment, network quality data includes: estimated bandwidth, network latency, network jitter, packet loss rate, and link cost.

[0058] Estimated bandwidth represents the currently available download speed, measured in Mbps, and is a dynamically changing metric.

[0059] Network latency is measured by the PING value; the lower the value, the lower the latency, which affects the efficiency of connection establishment.

[0060] Network jitter describes the fluctuation in the arrival time of data packets during network transmission. High jitter is very detrimental to transmission stability.

[0061] Packet loss rate represents the proportion of data packets lost during transmission.

[0062] Link cost is a non-technical metric, but it is crucial to user experience.

[0063] The weighted scoring model constructed based on the above network quality data is as follows:

[0064]

[0065] In the formula, For the overall quality score, For normalization function, To estimate bandwidth, Due to network latency, For network jitter, For packet loss rate, These are the weighting coefficients for estimated bandwidth, network latency, network jitter, packet loss rate, and link cost, respectively. For link costs, such as 4G / 5G A value of 0.3 indicates that it is not recommended but usable, while WiFi... Setting the value to 0 indicates that there is no link cost.

[0066] It is important to note that the weighting coefficients for each network quality data point are dynamically allocated based on the size of the upgrade package. Specifically: if the upgrade package size is less than the first threshold, it is defined as a small upgrade package, and the weighting is biased towards network latency and network jitter; if the first threshold is less than or equal to the upgrade package size but less than the second threshold, it is defined as a medium upgrade package, and the weighting is biased towards estimated bandwidth, network latency, and cost; if the upgrade package size is greater than or equal to the second threshold, it is defined as a large upgrade package, and the weighting is biased towards estimated bandwidth and packet loss rate.

[0067] In the description of this invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0068] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0069] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for intelligent upgrading of excavators, characterized in that, The user downloads the upgrade package required for the target excavator to the local application. After the local application establishes a connection with the target excavator's vehicle-side system and completes authentication, it sends the upgrade command to the human-machine interaction system in the vehicle-side system. After receiving the upgrade command, the human-computer interaction system obtains the priority of each available signal source and performs a stability determination on each signal source. Select the highest priority signal source from the stable signal sources as the download channel, and download the upgrade package data from the local application; After verification, the upgrade package data is transferred to the target component, and the regular upgrade process is executed.

2. The excavator intelligent upgrade method according to claim 1, characterized in that, The process of obtaining the priority of each available signal source includes: S1: Filter the currently available download signal sources to obtain a set of candidate signal sources; S2: Collect network quality data for each signal source in the candidate signal source set, and normalize the network quality data; S3: Input the normalized network quality data into the weighted scoring model, and combine the weight coefficients of each network quality data to obtain the comprehensive quality score of each candidate signal source; S4: Set the priority of each candidate signal source according to the overall quality score from high to low.

3. The excavator intelligent upgrade method according to claim 2, characterized in that, The network quality data includes: estimated bandwidth, network latency, network jitter, packet loss rate, and link cost.

4. The excavator intelligent upgrade method according to claim 2, characterized in that, The weighting coefficients for each network quality data point are dynamically allocated based on the upgrade package size, specifically as follows: If the upgrade package size is less than the first threshold, it is defined as a small package, and the weight configuration is biased towards network latency and network jitter; If the first threshold is less than or equal to the upgrade package size and less than the second threshold, it is defined as a medium-sized package, and the weight configuration is biased towards estimated bandwidth, network latency, and cost. If the upgrade package size is greater than or equal to the second threshold, it is defined as a large package, and the weight configuration is biased towards the estimated bandwidth and packet loss rate.

5. The excavator intelligent upgrade method according to claim 3, characterized in that, The weighted scoring model is as follows: ； In the formula, For the overall quality score, For normalization function, To estimate bandwidth, Due to network latency, For network jitter, For packet loss rate, For link cost, These are the weighting coefficients for estimated bandwidth, network latency, network jitter, packet loss rate, and link cost, respectively.

6. The excavator intelligent upgrade method according to claim 1, characterized in that, The stability determination of each signal source is as follows: if the packet loss rate of the signal source is not greater than the third threshold and the network jitter is not greater than the fourth threshold, then the signal source is determined to be stable; otherwise, the signal source is determined to be unstable.

7. The excavator intelligent upgrade method according to claim 1, characterized in that, Also includes: During the download process, continuously monitor the predicted remaining time for the current download channel; If the remaining prediction time for the current download channel exceeds the total prediction download time for other candidate signal sources, or if the current download channel's network is disconnected, the current download channel will be automatically paused, and the download will be switched to the next priority signal source.

8. The excavator intelligent upgrade method according to claim 1, characterized in that, Before transmitting the upgrade package data to the target component, the process also includes: obtaining current vehicle operating condition information and determining whether the conditions for a safety upgrade are met; Only when the vehicle's operating condition information meets the conditions for a safety upgrade will the upgrade package data be transmitted to the target component via the original vehicle's communication network.

9. The excavator intelligent upgrade method according to any one of claims 1-8, characterized in that, The human-machine interaction system includes: a communication unit, a main control computing unit, a vehicle data acquisition unit, and a memory; The communication unit integrates multiple communication modules; The main control computing unit runs the core programs of the operating system and algorithms; The vehicle data acquisition unit obtains vehicle operating condition information via the CAN bus; The memory is used to store downloaded upgrade packages and algorithm execution data.

10. The excavator intelligent upgrade method according to claim 9, characterized in that, The communication unit integrates a WiFi module, a Bluetooth module, a 4G / 5G module, and a USB interface.

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