PLC program upgrading and direct current screen compatibility improving method

Abstract

The invention belongs to the electrical field, and relates to a PLC program upgrading and direct current screen compatibility improving method, which comprises the following steps of: upgrading PLC program hardware and software, adopting a modular design and an intelligent monitoring system, optimizing battery management, improving electromagnetic compatibility, standardizing an interface and a protocol, using middleware or a gateway and the like. Performance and compatibility of the PLC and the direct current screen can be effectively improved, and stable operation of a power system is ensured.

Description

Technical Field

[0001] The present invention belongs to the electrical field and relates to a method for improving the compatibility between PLC program upgrade and DC power supply panel. Background Art

[0002] With the development of industrial automation and power system intelligence, the DC power supply panel system, as a key power supply device, is widely used in scenarios such as substations, rail transit, and data centers. Its core function is to provide a stable DC power supply for relay protection devices, circuit breaker operating mechanisms, etc. However, in practical applications, the compatibility upgrade of the DC power supply panel system faces the following technical bottlenecks:

[0003] 1. Excessive coupling between hardware and software: The traditional DC power supply panel system adopts a tightly coupled design of a dedicated charging module and a PLC. There are privatized encapsulation differences in the communication protocols (such as Modbus, CAN bus) of devices from different manufacturers. When the original factory charging module is out of production or needs to be replaced with a new model, the PLC program cannot be directly adapted due to protocol mismatch and inconsistent interface parameters, forcing enterprises to replace the entire hardware, resulting in a sharp increase in transformation costs (the single - upgrade cost can reach the million - yuan level).

[0004] 2. Insufficient generalization ability of control algorithms: Existing PLC programs are mostly developed based on specific hardware configurations, and their current balancing algorithms and voltage regulation logics are deeply bound to the electrical characteristics of fixed - model charging modules. For example, when the aging degrees of parallel modules are inconsistent or heterogeneous devices are replaced, traditional PID control is difficult to achieve dynamic load distribution, easily leading to over - limit current sharing deviation (>5%), causing module overload damage or even system downtime.

[0005] 3. Lagging upgrade verification means: Currently, the industry generally uses the "on - site trial - and - error method" for compatibility testing, that is, directly debugging the upgraded PLC program on physical devices, lacking the pre - verification ability for extreme working conditions (such as voltage transient impact, EMI interference). According to statistics, about 70% of the DC power supply panel downtime accidents caused by program logic defects can be avoided in advance through offline simulation, but the existing technology lacks a collaborative verification mechanism for digital twin and real - time systems.

[0006] 4. Lack of intelligent operation and maintenance: Old - fashioned DC power supply panel systems usually only have basic fault alarm functions, lack the ability to predict gradual faults such as insulation deterioration and abnormal current sharing of modules, and cannot achieve remote program iteration. In the scenario of cross - brand replacement of equipment, maintenance personnel need to manually configure parameters, which takes up to several days, seriously affecting power supply continuity.

[0007] The prior art also proposes to achieve multi-device access through a protocol converter, but it does not solve the problem of dynamic adaptation between the control algorithm and the hardware parameters, and manual intervention in parameter configuration is still required; an improved droop control algorithm is adopted to improve the current sharing accuracy, but its model does not consider the factor of module aging, and the current sharing performance decreases significantly after long-term operation; the DC panel upgrade scheme relies on a dedicated configuration tool and cannot be compatible with third-party devices, resulting in users being locked in a single supply chain system.

[0008] Under this background, there is an urgent need for a PLC program upgrade method that integrates protocol adaptation, algorithm reconstruction, simulation verification, and intelligent operation and maintenance to solve the compatibility problem of the DC panel system in the scenario of mixed use of multi-brand devices, reduce the upgrade cost, and improve the system reliability. Summary of the Invention

[0009] In view of this, the purpose of the present invention is to provide a method for upgrading PLC programs and improving the compatibility of DC panels to solve the existing problems.

[0010] To achieve the above object, the present invention provides the following technical solution: A method for upgrading PLC programs and improving the compatibility of DC panels realizes system adaptation through progressive technical links, including the following steps:

[0011] (1) System topology analysis and interface definition: Reverse-analyze the electrical topology structure of the target DC panel, identify the physical interface types, signal transmission paths, and key detection nodes of the PLC and the charging module, and generate an interface mapping table containing voltage / current sampling points;

[0012] (2) Two-way adaptation of communication protocols: Based on the interface mapping table in step (1), analyze the data frame structure of the DC panel's private communication protocol, construct a dual-channel protocol converter for Modbus RTU and CAN bus, and realize the real-time encoding and verification of PLC instructions into DC panel data packets;

[0013] (3) Construction of a dynamic compatibility parameter library: According to the protocol specifications analyzed in step (2), establish a compatibility database for multi-brand charging modules in the PLC, store the rated parameters, fault code mapping relationships, and historical operation characteristic data, and set up a parameter self-learning interface;

[0014] (4) Reconstruction of the control kernel and algorithm optimization: Based on the database parameters in step (3), reconstruct the PLC program kernel, integrate a fuzzy PID current equalization algorithm, a dynamic voltage compensation module, and an insulation impedance prediction model, where the current equalization algorithm dynamically adjusts the weight coefficient according to the degree of module aging;

[0015] (5) Digital twin simulation and verification: Using the topological structure in step (1) and the control algorithm in step (4), build a digital twin platform for multi-module parallel connection of DC power supplies in Matlab / Simulink, simulate the composite working conditions of temperature change from -25°C to 70°C, voltage fluctuation of ±20%, and load mutation, and verify the robustness of the control logic;

[0016] (6) Online diagnosis and closed-loop self-healing: Set threshold rules based on the simulation results in step (5), deploy a real-time diagnosis unit, and trigger insulation degradation warning, module hot plug detection, and dynamic compensation of control parameters by comparing the PLC output instructions with the feedback data of the DC power supply to form a closed-loop fault response;

[0017] (7) Human-computer interaction and status visualization: Associate the diagnosis data in step (6) with the database in step (3), generate a compatibility monitoring view on the HMI interface, and dynamically display the current sharing deviation rate of each module, protocol matching degree, and temperature distribution in the form of a 3D thermal map;

[0018] (8) Remote collaborative operation and maintenance integration: Upload the monitoring data in step (7) to the cloud platform through the OPC UA protocol, construct a device health assessment model, and support remote program iterative upgrade, energy efficiency optimization strategy push, and sharing of fault case libraries.

[0019] Optionally, the protocol converter in step (2) adopts frame structure dynamic recombination technology, specifically including: expanding the 03 function code register in the Modbus RTU protocol, adding dedicated fields for temperature monitoring and fan speed; adding a timestamp synchronization mechanism for the CAN bus protocol, and ensuring that the data acquisition time deviation of multiple modules ≤ 1.5ms through hardware interruption.

[0020] Optionally, the fuzzy PID current equalization algorithm in step (4) includes the following associated logics:

[0021] a) Based on the current detection nodes identified in step (1), obtain the real-time output current of the parallel modules at a sampling frequency of 5kHz;

[0022] b) Calculate the aging coefficient according to the module running hours in the database in step (3), and dynamically adjust the current distribution weight of each module;

[0023] c) When it is detected that the current deviation between modules exceeds ±1.8% and lasts for 8 seconds, automatically call the closed-loop self-healing mechanism in step (6) for priority switching.

[0024] Optionally, the simulation platform in step (5) includes a multi-dimensional coupling test module, whose input parameters are inherited from the database in step (3), and the test scenarios include: analysis of the influence of the internal resistance change of the battery pack on the resonance frequency of the charging module; verification of the power gradient derating strategy based on the voltage compensation module in step (4) when the cooling fan stops rotating; statistics of the bit error rate of the protocol converter under electromagnetic interference and fault tolerance optimization.

[0025] Optionally, the closed-loop self-healing mechanism in step (6) implements three-level collaborative protection: primary warning: when the insulation resistance value drops to 800 kΩ, trigger an HMI warning and record it in the database in step (3); intermediate intervention: when the detected module current sharing deviation > 4%, automatically enable the standby module and synchronously update the weight coefficient in step (4); emergency protection: when the DC bus voltage exceeds 115% of the rated value for 0.3 seconds, cut off the main circuit and upload the fault data to the cloud platform in step (8).

[0026] Optionally, the compatibility database in step (3) integrates an incremental learning function, and the specific logic includes: collecting the nameplate parameters of newly connected modules through the protocol converter in step (2), automatically generating device feature vectors and expanding database entries; combining the historical fault data in step (6), and using the random forest algorithm to optimize the threshold decision rule in the control model in step (4).

[0027] Optionally, the HMI interface in step (7) adopts augmented reality-assisted diagnosis, and the specific implementation method is: scanning the device QR code to retrieve the topology wiring diagram generated in step (1), and overlaying and displaying the real-time signal flow path of the PLC and the DC panel; comparing the heat distribution prediction data in the simulation result of step (5) with the real-time temperature sampling value, and identifying the overheat risk area with a color scale map.

[0028] Optionally, a hardware abstraction layer (HAL) is embedded in the PLC program kernel in step (4), and its functions include: abstracting the physical interfaces defined in step (1) into standardized virtual device nodes; providing a unified driver interface through the protocol converter in step (2) to support the plug-and-play adaptation of third-party charging modules.

[0029] The beneficial effects of the present invention are as follows:

[0030] 1) Seamless compatibility of multi-brand devices: Through the design of protocol bidirectional mapping and hardware abstraction layer, break through the private protocol barriers, support the plug-and-play access of charging modules from mainstream manufacturers, significantly improve the compatibility coverage rate, and avoid the risk of system reconstruction caused by the discontinuation of hardware from a single manufacturer. The incremental learning function of the dynamic parameter library can automatically analyze the electrical parameters of newly connected modules and optimize the control logic, greatly shortening the manual configuration time and significantly improving the device interchange efficiency.

[0031] 2) Dynamic control algorithms enhance system performance: The current equalization algorithm that integrates fuzzy PID and aging coefficient compensation adjusts the weight distribution in real time according to the module status, significantly improving the current sharing accuracy in scenarios where new and old modules are mixed, and effectively extending the service life of the equipment. The dynamic voltage compensation module can adapt to grid fluctuations and load mutations, maintaining the DC bus voltage highly stable in scenarios with wide-range voltage fluctuations and ensuring the power supply safety of the backend equipment.

[0032] 3) Full-condition simulation pre-verification reduces operation and maintenance risks: The digital twin platform exposes the logical defects of the PLC program in extreme environments and interference scenarios in advance through multi-physical field coupling tests, significantly reducing the failure rate of on-site commissioning and avoiding major downtime losses. The simulation results are linked with the real-time diagnosis system to optimize the fault threshold setting, greatly advancing the warning time for gradual faults such as insulation degradation and module overload.

[0033] 4) Intelligent operation and maintenance and rapid response: The combination of the three-level fault response mechanism and the augmented reality HMI significantly shortens the fault location time and effectively improves the maintenance efficiency. The cloud platform supports remote program hot upgrades and energy efficiency strategy pushes, reducing the on-site maintenance frequency, significantly lowering the annual operation and maintenance cost, and realizing cross-system knowledge collaboration through the sharing of case libraries.

[0034] 5) Optimization of the total life cycle cost: By decoupling the software and hardware dependencies through the hardware abstraction layer, the cost of upgrading the PLC program is significantly reduced, and at the same time, the service life of the existing equipment is extended. The modular design supports local function iteration, avoiding redundant investment in full-system replacements and effectively controlling the cost of single compatibility transformations.

[0035] Through the synergistic effects of protocol compatibility breakthroughs, algorithm optimization, digital twin verification, and intelligent operation and maintenance systems, this method achieves the technical effect of "one upgrade, long-term compatibility" while ensuring system reliability. Practical engineering applications show that this method can significantly reduce the number of system failures, improve equipment utilization, and greatly shorten the investment return period, with outstanding economic and industry promotion value.

[0036] Other advantages, objectives, and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the following specification. Detailed implementation manners

[0037] The following uses specific concrete examples to illustrate the implementation manners of the present invention. Those skilled in the art can easily understand the other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0038] In this embodiment, the background is the No. 3 unit of the longevity gas production base. Due to the aging of the original charging modules in its DC panel system and the discontinuation of spare parts production, equipment failures frequently occur, affecting the safe and stable operation of the unit. To solve this problem, the project team decided to upgrade and transform the DC panel system, especially to improve the compatibility of the PLC program with the new charging modules.

[0039] Specific Example 1

[0040] In this embodiment, its specific implementation steps include:

[0041] (1) System topology analysis and interface definition

[0042] First, the project team performed reverse analysis on the electrical topology of the target DC panel, identified the physical interface types, signal transmission paths, and key detection nodes of the PLC and the charging modules. Through this step, an interface mapping table containing voltage / current sampling points was generated, providing basic data support for the subsequent steps.

[0043] (2) Bidirectional adaptation of communication protocols

[0044] Based on the interface mapping table, the project team analyzed the data frame structure of the DC panel's private communication protocol and constructed a dual-channel protocol converter for Modbus RTU and CAN bus. This converter realized the real-time encoding and verification of PLC instructions into DC panel data packets, ensuring seamless communication between different brand charging modules and the PLC.

[0045] Specific implementation: In the Modbus RTU protocol, the 03 function code register was extended, and dedicated fields for temperature monitoring and fan speed were added; a timestamp synchronization mechanism was added to the CAN bus protocol, ensuring that the time deviation of multi-module data acquisition was ≤1.5 ms through hardware interrupts.

[0046] (3) Construction of a dynamic compatibility parameter library

[0047] According to the protocol specifications, the project team established a compatibility database for multi-brand charging modules in the PLC. This database stores rated parameters, fault code mapping relationships, and historical operation characteristic data, and sets a parameter self-learning interface. This step provides data support for the subsequent optimization of control algorithms.

[0048] (4) Control Kernel Reconstruction and Algorithm Optimization

[0049] Based on the compatibility database parameters, the project team reconstructed the PLC program kernel and integrated the fuzzy PID current balancing algorithm, dynamic voltage compensation module, and insulation impedance prediction model. Among them, the fuzzy PID current balancing algorithm dynamically adjusts the weight coefficient according to the module aging degree, ensuring the current sharing accuracy in the scenario of mixing different new and old modules.

[0050] Specific implementation: The real-time output current of the parallel modules is obtained by using a sampling frequency of 5 kHz; the aging coefficient is calculated according to the module running hours in the database, and the current distribution weight of each module is dynamically adjusted; when the current deviation between modules exceeds ±1.8% and lasts for 8 seconds, the closed-loop self-healing mechanism is automatically called for priority switching.

[0051] (5) Digital Twin Simulation Verification

[0052] Using the system topology structure and control algorithm, the project team built a digital twin platform for multi-module parallel connection of DC power panels in Matlab / Simulink. This platform simulated the composite working conditions of temperature change from -25°C to 70°C, voltage fluctuation of ±20%, and load mutation, and verified the robustness of the control logic.

[0053] Specific implementation: The simulation platform includes a multi-dimensional coupling test module, and its input parameters are inherited from the compatibility database. The test scenarios include the analysis of the influence of the internal resistance change of the battery pack on the resonance frequency of the charging module, the verification of the power gradient load reduction strategy when the cooling fan stops rotating, and the error rate statistics and fault tolerance optimization of the protocol converter under electromagnetic interference.

[0054] (6) Online Diagnosis and Closed-Loop Self-Healing

[0055] Based on the simulation results, the project team set threshold rules and deployed a real-time diagnosis unit. By comparing the PLC output instructions with the DC power panel feedback data, this unit can trigger insulation deterioration warnings, module hot plug detection, and dynamic compensation of control parameters, forming a closed-loop for fault response.

[0056] Specific implementation: A three-level collaborative protection mechanism was implemented. The primary warning triggers an HMI warning and records it in the database when the insulation resistance value drops to 800 kΩ; the intermediate intervention automatically enables the standby module and synchronously updates the weight coefficient when the module current sharing deviation > 4% is detected; the emergency protection cuts off the main circuit and uploads the fault data to the cloud platform when the DC bus voltage exceeds 115% of the rated value and lasts for 0.3 seconds.

[0057] (7) Human-Machine Interaction and Status Visualization

[0058] After associating the diagnostic data with the database, the project team generated a compatibility monitoring view on the HMI interface. This view dynamically displays the current sharing deviation rate of each module, the protocol matching degree, and the temperature distribution in the form of a 3D thermal map, providing intuitive device status information for the operation and maintenance personnel.

[0059] Specific implementation: The HMI interface adopts augmented reality-assisted diagnosis technology. By scanning the device QR code, the topological wiring diagram is retrieved and the real-time signal flow path of the PLC and the DC power supply panel is superimposed and displayed; the heat distribution prediction data in the simulation results is compared with the real-time temperature sampling values, and the overheating risk areas are marked with a color scale map.

[0060] (8) Remote collaborative operation and maintenance integration

[0061] Through the OPC UA protocol, the project team uploads the monitoring data to the cloud platform and constructs a device health assessment model. This model supports remote program iterative upgrade, energy efficiency optimization strategy push, and fault case library sharing, realizing intelligent operation and maintenance.

[0062] Specific embodiment 2

[0063] After the implementation of the above steps, the DC power supply panel system of Unit 3 in the Changshou Gas Production Base has successfully completed the upgrade and transformation. The new system not only improves the stability and reliability of the equipment, but also significantly reduces the spare parts inventory and capital occupancy rate. Through digital twin simulation verification and the establishment of an intelligent operation and maintenance system, the project team has effectively reduced the operation and maintenance risks and improved the equipment utilization rate. At the same time, the implementation of this project also provides a successful case and reference for the upgrade and transformation of similar DC power supply panel systems.

[0064] Economic benefits: Through the upgrade and transformation, the loss caused by the unit shutdown due to the DC power supply panel failure is avoided, and it is expected to create direct economic benefits of about 900,000 yuan per year. At the same time, the service life of the equipment is extended, and the equipment procurement and operation and maintenance costs are reduced.

[0065] Social benefits: The generality and interchangeability of equipment spare parts are improved, and the risk of dependence on a single supplier is reduced. At the same time, through the establishment of an intelligent operation and maintenance system, the intelligent level of equipment operation is improved, providing strong support for the intelligent transformation of the industry.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the present technical solution, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A method for improving the compatibility between PLC program upgrade and DC power supply panel, characterized in that The system adaptation is achieved through progressive technical steps, including the following steps: (1) System topology analysis and interface definition: Reverse-analyze the electrical topology of the target DC power supply panel, identify the physical interface types, signal transmission paths, and key detection nodes of the PLC and charging modules, and generate an interface mapping table containing voltage / current sampling points; (2) Bidirectional adaptation of communication protocols: Based on the interface mapping table in step (1), analyze the data frame structure of the private communication protocol of the DC power supply panel, construct a dual-channel protocol converter for Modbus RTU and CAN bus, and realize the real-time encoding and verification of PLC instructions into DC power supply panel data packets; (3) Construction of a dynamic compatibility parameter library: According to the protocol specifications analyzed in step (2), establish a compatibility database for multi-brand charging modules in the PLC, store rated parameters, fault code mapping relationships, and historical operation characteristic data, and set up a parameter self-learning interface; (4) Reconstruction of the control kernel and optimization of the algorithm: Based on the database parameters in step (3), reconstruct the PLC program kernel, integrate a fuzzy PID current balancing algorithm, a dynamic voltage compensation module, and an insulation impedance prediction model, where the current balancing algorithm dynamically adjusts the weight coefficient according to the aging degree of the module; (5) Digital twin simulation verification: Utilize the topology in step (1) and the control algorithm in step (4) to build a digital twin platform for parallel connection of multiple modules of the DC power supply panel in Matlab / Simulink, simulate composite working conditions of temperature change from -25°C to 70°C, voltage fluctuation of ±20%, and load mutation, and verify the robustness of the control logic; (6) Online diagnosis and closed-loop self-healing: Set threshold rules based on the simulation results in step (5), deploy a real-time diagnosis unit, trigger insulation degradation warning, module hot-swap detection, and dynamic compensation of control parameters by comparing PLC output instructions with DC power supply panel feedback data, and form a closed-loop for fault response; (7) Human-machine interaction and status visualization: Associate the diagnosis data in step (6) with the database in step (3), generate a compatibility monitoring view on the HMI interface, and dynamically display the current sharing deviation rate, protocol matching degree, and temperature distribution in the form of a 3D heat map of each module; (8) Remote collaborative operation and maintenance integration: Upload the monitoring data in step (7) to the cloud platform through the OPC UA protocol, construct a device health assessment model, and support remote program iterative upgrade, energy efficiency optimization strategy push, and sharing of a fault case library.

2. A method for improving the compatibility between PLC program upgrade and DC panel according to claim 1, characterized in that: The protocol converter described in step (2) adopts frame structure dynamic recombination technology, specifically including: expanding the 03 function code register in the Modbus RTU protocol, adding dedicated fields for temperature monitoring and fan speed; adding a timestamp synchronization mechanism for the CAN bus protocol, and ensuring that the data acquisition time deviation of multiple modules ≤1.5ms through hardware interrupt.

3. A method for upgrading a PLC program and improving the compatibility with a DC panel according to claim 1, characterized in that: The fuzzy PID current balancing algorithm described in step (4) includes the following associated logics: a) Based on the current detection nodes identified in step (1), obtain the real-time output current of parallel modules at a sampling frequency of 5kHz; b) Calculate the aging coefficient according to the module operation hours in the database in step (3), and dynamically adjust the current distribution weight of each module; c) When the current deviation between modules is detected to exceed ±1.8% for 8 consecutive seconds, the closed-loop self-healing mechanism in step (6) is automatically invoked for priority switching.

4. A method for upgrading a PLC program and improving the compatibility with a DC panel according to claim 1, characterized in that: The simulation platform in step (5) includes a multi-dimensional coupling test module, whose input parameters are inherited from the database in step (3). The test scenarios include: analysis of the influence of the internal resistance change of the battery pack on the resonant frequency of the charging module; verification of the power gradient load reduction strategy based on the voltage compensation module in step (4) when the cooling fan stops rotating; statistics of the bit error rate of the protocol converter under electromagnetic interference and fault tolerance optimization.

5. A method for upgrading a PLC program and improving the compatibility with a DC panel according to claim 1, characterized in that: The closed-loop self-healing mechanism in step (6) implements three-level collaborative protection: primary warning: when the insulation resistance value drops to 800 kΩ, trigger an HMI warning and record it in the database in step (3); intermediate intervention: when the module current sharing deviation > 4% is detected, automatically enable the standby module and synchronously update the weight coefficient in step (4); emergency protection: when the DC bus voltage exceeds 115% of the rated value for 0.3 seconds, cut off the main circuit and upload the fault data to the cloud platform in step (8).

6. A method for upgrading a PLC program and improving the compatibility of a DC panel according to claim 1, characterized in that: The compatibility database in step (3) integrates an incremental learning function. The specific logic includes: collecting the nameplate parameters of newly connected modules through the protocol converter in step (2), automatically generating device feature vectors and expanding the database entries; combining the historical fault data in step (6), and optimizing the threshold determination rule in the control model in step (4) using the random forest algorithm.

7. A method for improving the compatibility between PLC program upgrade and DC panel according to claim 1, characterized in that: The HMI interface in step (7) adopts augmented reality-assisted diagnosis. The specific implementation method is: scanning the device QR code to retrieve the topological wiring diagram generated in step (1), and overlaying and displaying the real-time signal flow path of the PLC and the DC power supply panel; comparing the heat distribution prediction data in the simulation results of step (5) with the real-time temperature sampling values, and identifying the overheating risk area with a color scale map.

8. A method for improving the compatibility between PLC program upgrade and DC panel according to claim 1, characterized in that: Embed a hardware abstraction layer (HAL) in the PLC program kernel in step (4). Its functions include: abstracting the physical interfaces defined in step (1) into standardized virtual device nodes; providing a unified driver interface through the protocol converter in step (2) to support the plug-and-play adaptation of third-party charging modules.