Electric tricycle controller circuit board welding quality monitoring system

Abstract

The invention discloses an electric tricycle controller circuit board welding quality monitoring system, and relates to the technical field of welding quality monitoring, and the system comprises a power unit connected with a target electric tricycle; establishing a circuit simulation model based on the target electro-tricycle; welding quality characteristic indexes are recognized, parameter drift analysis is conducted, and a first parameter drift set is determined; performing parameter drift analysis on connection between an electric power conversion assembly in the power unit and an electric tricycle controller to obtain a second parameter drift set; and establishing a welding quality evaluation model. The technical problems that effective monitoring is lacked in the welding process of the electric tricycle controller circuit board and the welding quality cannot be accurately evaluated in the prior art are solved, and the effects of comprehensively monitoring the welding process of the electric tricycle controller circuit board, accurately evaluating the welding quality, effectively identifying potential fault points and improving the welding quality of the electric tricycle controller circuit board are achieved. Therefore, the welding quality of the power unit of the electro-tricycle is guaranteed, and the performance and reliability of the whole tricycle are improved.

Description

Technical Field

[0001] The invention relates to the technical field of welding quality monitoring, and in particular to a welding quality monitoring system for a circuit board of a controller of an electric tricycle. Background Art

[0002] With the widespread application of electric tricycles in logistics, transportation, short-distance travel and other fields, their performance and reliability have attracted much attention. As one of the core components of the electric tricycle controller, the welding quality of its circuit board directly affects the function of the controller and the performance of the whole vehicle. In the current production process of electric tricycles, there are many technical challenges in the welding of the controller circuit board. Traditional welding quality control methods mainly rely on manual sampling, which is not only inefficient but also highly subjective, and it is difficult to ensure that the welding quality of each circuit board can be effectively monitored. Due to the lack of real-time and comprehensive monitoring methods, during the welding process, the changes in key factors such as solder joint morphology, soldering temperature and soldering amount cannot be accurately grasped in a timely manner. For example, poor solder joint morphology may lead to increased contact resistance and affect the efficiency of power transmission; too high or too low soldering temperature may cause problems such as cold soldering and excessive oxidation of solder, reducing the mechanical strength and conductivity of the solder joint; unreasonable soldering amount may cause short circuit risks or loose solder joint connections.

[0003] The existing technology has technical problems such as lack of effective monitoring during the welding process of the electric tricycle controller circuit board and inability to accurately evaluate the welding quality. Summary of the invention

[0004] The present application provides an electric tricycle controller circuit board welding quality monitoring system, which is used to solve the technical problems in the prior art of lack of effective monitoring and inability to accurately evaluate welding quality during the electric tricycle controller circuit board welding process.

[0005] In view of the above problems, the present application provides an electric tricycle controller circuit board welding quality monitoring system.

[0006] The present application provides an electric tricycle controller circuit board welding quality monitoring system, the system comprising: A power unit connection module, the power unit connection module is used to connect the power unit of the target electric tricycle, the power unit includes a motor component, a power conversion component, and an electric tricycle controller; a circuit simulation model establishment module, the circuit simulation model establishment module is based on the target electric tricycle, and establishes a circuit simulation model, the circuit simulation model includes multiple control loops, and marks a number of welding points on each control loop; a welding monitoring unit adoption module, the welding monitoring unit adoption module is used to adopt a welding monitoring unit to perform welding synchronous monitoring on each control loop, and collect a monitoring data set, the monitoring data set includes a solder point morphology subset, a solder temperature subset, and a solder quantum set, and the welding monitoring unit is deployed on a welding workbench; a first parameter drift set determination module, the first parameter drift set determination module is used to parse the solder point morphology subset, the solder temperature subset, and the solder quantum set, and identify the welding quality characteristic index The invention relates to a welding quality evaluation model building module, wherein the welding quality evaluation model building module comprises a welding quality evaluation model building module, wherein the welding quality evaluation model building module comprises a welding quality evaluation model building module, wherein the welding quality evaluation model building module builds a welding quality evaluation model based on the first parameter drift set and the first welding point potential fault queue, the second parameter drift set and the second welding point potential fault queue, and the welding quality evaluation model is used to provide welding quality monitoring reminders to the electric tricycle controller.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: A power unit connection module is connected to the power unit of the target electric tricycle; a circuit simulation model establishment module is based on the target electric tricycle, and a circuit simulation model is established; a welding monitoring unit adopting module is used to adopt the welding monitoring unit to perform welding synchronous monitoring on each control loop and collect monitoring data sets; a first parameter drift set determination module is used to parse the solder joint morphology subset, solder temperature subset, and solder quantum set, identify welding quality characteristic indicators, and perform parameter drift analysis on the connection between the motor component in the power unit and the electric tricycle controller according to the circuit simulation model, determine the first parameter drift set, and calibrate the first welding point potential fault queue; a second parameter drift set acquisition module is used to perform parameter drift analysis on the connection between the power conversion component in the power unit and the electric tricycle controller based on the welding quality characteristic indicators and the circuit simulation model, obtain the second parameter drift set, and calibrate the second welding point potential fault queue; a welding quality assessment model establishment module is used to establish a welding quality assessment model based on the first parameter drift set and the first welding point potential fault queue, the second parameter drift set and the second welding point potential fault queue. The technical effect of comprehensively monitoring the welding process of the electric tricycle controller circuit board, accurately evaluating the welding quality, and effectively identifying potential fault points has been achieved, thereby ensuring the welding quality of the electric tricycle power unit and improving the performance and reliability of the entire vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A structural schematic diagram of a welding quality monitoring system for an electric tricycle controller circuit board is provided for an embodiment of the present application.

[0010] Figure 2 A schematic diagram of the flow of establishing a circuit simulation model for a welding quality monitoring system for a controller circuit board of an electric tricycle is provided for an embodiment of the present application.

[0011] Explanation of the reference numerals: power unit connection module 10 , circuit simulation model establishment module 20 , welding monitoring unit adoption module 30 , first parameter drift set determination module 40 , second parameter drift set acquisition module 50 , welding quality assessment model establishment module 60 . DETAILED DESCRIPTION

[0012] The present application provides an electric tricycle controller circuit board welding quality monitoring system, which is used to solve the technical problems in the prior art of lack of effective monitoring and inability to accurately evaluate welding quality during the electric tricycle controller circuit board welding process.

[0013] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0014] Examples, such as Figure 1 As shown, the present application provides an electric tricycle controller circuit board welding quality monitoring system, the system comprising: The power unit connection module 10 is used to connect the power unit of the target electric tricycle, and the power unit includes a motor assembly, a power conversion assembly, and an electric tricycle controller.

[0015] Specifically, the power unit connection module 10 establishes a stable and reliable connection link with the target electric tricycle power unit. This power unit covers the motor assembly that is crucial to the operation of the vehicle, the power conversion assembly responsible for the conversion of electric energy, and the electric tricycle controller that plays a core control role. The power unit connection module 10 accurately realizes electrical connection with the motor assembly through a carefully designed adapter interface and high-quality connection cables, ensuring that the electrical signals related to the motor operation status, such as the motor speed feedback signal, torque signal, etc., can be accurately obtained, so as to accurately monitor the cooperative working state between the motor and the controller in the future. When connected to the power conversion assembly, the unimpeded power transmission line is guaranteed. Whether it is from the battery to the controller, or in the process of supplying power to the motor under the control of the controller, the changes in parameters such as current and voltage can be accurately monitored, thereby providing a reliable data source for evaluating the power conversion efficiency and stability. For the connection of the electric tricycle controller, the power unit connection module 10 ensures the accurate transmission of the control signal, so that the monitoring system can obtain the output instructions of the controller in real time, as well as the control information of the controller on the motor assembly and the power conversion assembly, laying a solid foundation for a comprehensive analysis of the working state of the entire power unit. Through this comprehensive and precise connection method, the power unit connection module 10 provides a stable data transmission channel for subsequent circuit simulation model establishment, welding quality monitoring and evaluation, etc., ensuring that the entire monitoring system can operate accurately and efficiently, and effectively guaranteeing the reliability and stability of the welding quality of the electric tricycle power unit.

[0016] The circuit simulation model building module 20 builds a circuit simulation model based on the target electric tricycle, wherein the circuit simulation model includes a plurality of control loops and marks a plurality of welding points on each control loop.

[0017] Specifically, first, the basic model parameters of the target electric tricycle are comprehensively collected, including the rated output power and speed range of the motor component, which are key factors in determining the working characteristics and performance requirements of the motor; the rated conversion current and current capacity of the power conversion component, which are related to the efficiency and stability of the power conversion; and the rated control voltage and voltage range of the electric tricycle controller, which are crucial for the normal operation of the controller and the precise control of other components. Based on these detailed basic model parameters, a basic model architecture is constructed, which fully considers the load working state of the electric tricycle in different operating scenarios, such as the high current impact state at startup, the dynamic load change state during acceleration, the stable load state during uniform speed driving, and the energy recovery related load state during deceleration. In order to make the model more in line with the actual operating conditions, the module further uses rich historical operating parameters to deeply optimize the basic model architecture. Through a detailed analysis of the historical operating parameters, such as scientific sorting in the order of the load working state duration from long to short, multiple historical operating parameter subsets closely related to different load working states are obtained. At the same time, combined with carefully planned routine usage scenarios, such as the initial current change of the motor in the starting usage scenario, the torque demand change in the acceleration usage scenario, the stable power output of the uniform speed driving usage scenario, and the energy feedback characteristics of the deceleration usage scenario, this information is used to repeatedly iteratively train the basic model architecture. The final circuit simulation model can accurately present the complex characteristics of the target electric tricycle circuit system. The multiple control loops clearly included accurately depict the transmission path of current and signals in the entire circuit, and several welding points are accurately marked on each control loop. These welding points, as the key connection parts in the circuit, are the core focus of subsequent welding quality monitoring and analysis, providing an important structural foundation and theoretical basis for the comprehensive evaluation of welding quality, ensuring that the entire monitoring system can accurately and effectively monitor the welding quality of the electric tricycle controller circuit board.

[0018] The welding monitoring unit adopts module 30, and the welding monitoring unit adopts module 30 for adopting the welding monitoring unit to perform welding synchronous monitoring on each control loop and collect monitoring data sets, wherein the monitoring data sets include a solder point morphology subset, a solder temperature subset, and a solder quantum subset. The welding monitoring unit is deployed on a welding workbench.

[0019] Specifically, the welding monitoring unit uses module 30 to deploy an advanced welding monitoring unit on the welding workbench. With its high-precision sensors and intelligent monitoring system, the monitoring unit can perform real-time and synchronous welding monitoring of each control loop. During the welding operation, high-definition imaging technology and image analysis algorithms are used to accurately capture the morphological subset of the solder joints, and record in detail the key appearance features such as the shape, size, flatness, and connection status of the solder joints with surrounding components. These features are directly related to the physical structural integrity and electrical connection reliability of the solder joints. At the same time, through the built-in high-precision temperature sensor, the solder temperature subset is closely monitored, and the temperature change curve of the solder from the beginning of melting to the solidification process is tracked throughout the process. The temperature range during the welding process is strictly controlled, because the appropriate solder temperature is crucial to ensure the quality of welding and avoid problems such as cold soldering or overheating to damage components. In addition, with the help of advanced weight sensing or flow monitoring technology, the solder quantum set is accurately obtained to ensure that the amount of solder applied to each solder joint is just right. The right amount of solder can not only ensure good conductivity, but also provide sufficient mechanical strength to stabilize the solder joint. The comprehensive collection of these monitoring data sets covering multi-dimensional information such as solder joint morphology, solder temperature and solder quantity provides a rich data foundation for the subsequent in-depth analysis of welding quality. The welding monitoring unit adopts the effective operation of module 30, which enables the entire monitoring system to detect potential problems in time during the welding process, providing a strong preliminary guarantee for improving the welding quality of the electric tricycle controller circuit board, ensuring that each solder joint meets high-quality standards, thereby improving the performance and reliability of the controller and even the entire electric tricycle.

[0020] The first parameter drift set determination module 40 is used to parse the solder point morphology subset, solder temperature subset, and solder quantum set, identify welding quality characteristic indicators, perform parameter drift analysis on the connection between the motor assembly in the power unit and the electric tricycle controller according to the circuit simulation model, determine the first parameter drift set, and calibrate the potential fault queue of the first welding point.

[0021] Specifically, the first parameter drift set determination module 40 conducts in-depth analysis of the solder joint morphology subset, solder temperature subset, and solder quantum set collected by the welding monitoring unit. By using image processing algorithms, temperature data analysis models, and solder quantity statistical models, key characteristic indicators that affect welding quality, such as solder joint fullness and roundness, are accurately identified from the solder joint morphology subset; indicators that reflect the stability of the welding process, such as temperature fluctuation range and heating and cooling rates, are extracted from the solder temperature subset; characteristic indicators such as whether the solder quantity is within a reasonable range are determined from the solder quantum set. Based on the constructed circuit simulation model, this module focuses on the connection between the motor assembly in the power unit and the electric tricycle controller. With the help of the accurate description of the electrical characteristics and signal transmission logic of this connection link in the circuit simulation model, combined with the identified welding quality characteristic indicators, a comprehensive parameter drift analysis is performed on the connection. During the analysis, factors such as changes in contact resistance caused by poor solder joint morphology, changes in the metal structure of the solder joint caused by abnormal solder temperature that affect electrical parameters, and changes in conductivity caused by inappropriate solder quantity were considered. The impact of these factors on key parameters of the connection part (such as resistance, inductance, capacitance, etc.) was comprehensively evaluated to determine the first parameter drift set, which accurately quantifies the degree to which the parameters deviate from the normal range due to welding quality problems. At the same time, based on the parameter drift, the potential fault queue of the first welding point was calibrated by comparing with the preset thresholds and standards. It is clear which welding points have a higher potential failure risk due to large parameter drift, which provides a clear direction for subsequent targeted detection, repair or adjustment, effectively improving the efficiency and accuracy of troubleshooting welding quality problems between the motor assembly and the controller, and ensuring the reliability and stability of the key connection part of the electric tricycle power unit.

[0022] The second parameter drift set acquisition module 50 performs parameter drift analysis on the connection between the power conversion component in the power unit and the electric tricycle controller based on the welding quality characteristic index and the circuit simulation model, acquires the second parameter drift set, and calibrates the potential fault queue of the second welding point.

[0023] Specifically, the second parameter drift set acquisition module 50 is based on the welding quality characteristic indicators obtained and analyzed from the welding process. These indicators include information on solder joint morphology, solder temperature, solder quantity, etc., which fully reflect the quality level of the welding operation. With these rich indicator data, the work is carried out in depth based on the circuit simulation model. The circuit simulation model accurately depicts the key information such as the circuit structure, electrical characteristics and signal transmission path of the connection between the power conversion component in the power unit and the electric tricycle controller. The module combines the welding quality characteristic indicators with the circuit simulation model to perform a meticulous parameter drift analysis on this specific connection. Considering the importance of the power conversion component in the power conversion process and the accuracy requirements of the signal interaction between it and the controller, the influence of the solder joint morphology on the current conduction path is analyzed, such as whether the irregular solder joint shape will increase the contact resistance and thus affect the power conversion efficiency; the interference of solder temperature fluctuations on the performance of electronic components inside the power conversion component, and the resulting changes in electrical parameters; insufficient or excessive solder quantity on the connection stability and conductivity changes and other factors. Through calculation and simulation, the second parameter drift set is obtained, which accurately quantifies the degree of deviation of various parameters of this connection part from the normal standard due to welding quality problems. Then, according to the degree and trend of parameter drift, the potential fault queue of the second welding point is calibrated by strict comparison with the pre-set safety threshold and fault judgment criteria. The locations of welding points with high potential failure risks due to welding problems on the connection line between the power conversion component and the controller are clearly identified, which provides key technical support and decision-making basis for the subsequent timely and effective maintenance measures, ensuring the reliable connection between the power conversion component and the controller, and the stable operation of the entire electric tricycle power system.

[0024] A welding quality assessment model establishment module 60, the welding quality assessment model establishment module 60 establishes a welding quality assessment model based on the first parameter drift set and the first welding point potential fault queue, the second parameter drift set and the second welding point potential fault queue, and the welding quality assessment model is used to monitor the welding quality of the electric tricycle controller.

[0025] Specifically, the welding quality assessment model building module 60 uses the first parameter drift set and the corresponding first welding point potential fault queue, the second parameter drift set and the associated second welding point potential fault queue as key input information. By comprehensively considering the deviation of various parameters reflecting the connection part between the motor component and the electric tricycle controller in the first parameter drift set, such as resistance drift, inductance change value, capacitance fluctuation degree, etc., combined with the position of the welding point with possible problems specified by the first welding point potential fault queue, the welding quality status and potential risks of the connection link are comprehensively evaluated. At the same time, the parameter change data about the connection between the power conversion component and the controller in the second parameter drift set is deeply analyzed, including the drift of the stability of the parameters related to the power conversion, the accuracy of the signal transmission parameters, and the fault potential welding points indicated by the second welding point potential fault queue, so as to accurately grasp the welding quality status of this key connection part. On this basis, the support vector machine (SVM) algorithm is used to construct a welding quality assessment model. The model can receive various monitoring data from the actual welding process in real time, and accurately judge the welding quality level of the electric tricycle controller based on its internal complex logic and algorithm. When abnormal fluctuations in welding quality are detected, such as parameter drift beyond the safe range or increased risk of potential failure, the model will promptly issue a welding quality monitoring reminder and notify relevant personnel in the form of an intuitive alarm. According to the reminder, corresponding measures can be taken quickly, such as adjusting welding process parameters, repairing potential faulty welds, or strengthening quality inspection, etc., thereby effectively protecting the welding quality of the electric tricycle controller, ensuring the stable operation of the entire electric tricycle power system, and improving the reliability and safety of the product.

[0026] In one possible implementation, Figure 2 As shown, based on the target electric tricycle, a circuit simulation model is established, which also includes: The basic model parameters of the target electric tricycle are obtained, wherein the basic model parameters include the rated output power and speed range of the motor component, the rated conversion current and current capacity of the power conversion component, and the rated control voltage and voltage range of the electric tricycle controller; a basic model framework identified by the basic model parameters is established, wherein the basic model framework includes different load working states; the basic model framework is optimized through historical operating parameters to determine the circuit simulation model.

[0027] Specifically, in order to build an accurate circuit simulation model, the basic model parameters of the target electric tricycle are fully obtained. These parameters are the basis for model construction, among which the rated output power and speed range of the motor component are particularly critical. The rated output power determines the power that the motor can provide under normal working conditions. For example, if the rated output power of the motor is 1000W, it means that under ideal conditions, the motor can continuously and stably output 1000W of power to drive the vehicle. The speed range limits the working speed range of the motor. For example, the speed range is 0-3000rpm, which means that the motor can achieve different operating states within this speed range, from low speed at startup to high speed during driving. The rated conversion current and current capacity of the power conversion component are also indispensable. The rated conversion current determines the current that the component can safely and effectively handle during the power conversion process. For example, the rated conversion current is 20A, which means that the current passing through the component should fluctuate around this value during normal operation. The current capacity indicates the maximum current value that the component can withstand. If the current capacity is 30A, when the current exceeds this value, it will cause damage to the component. The rated control voltage and voltage range of the electric tricycle controller are important parameters to ensure the normal operation of the controller. The rated control voltage, such as 48V, is the standard voltage value designed for the controller, while the voltage range (such as 42V-54V) specifies the upper and lower limits of the voltage for the controller to work normally. When the actual voltage exceeds this range, the controller may not be able to accurately control the motor, affecting the vehicle performance.

[0028] The basic model parameters obtained are used as identifiers to establish a basic model architecture. This architecture is designed to simulate various working states of electric tricycles in actual operation, among which different load working states are the key considerations. For example, when starting, the motor needs to overcome a large static friction force, and it is in a high-load state at this time, with a large current demand; during acceleration, the vehicle requires additional power and the load is relatively high; when driving at a constant speed, the load is relatively stable, and the motor output power remains at a relatively constant level; when decelerating, the motor may be in a power generation state, converting the vehicle's kinetic energy into electrical energy and feeding it back to the battery, and the load state changes. The basic model architecture simulates these different load working states to build a basic framework that can reflect the actual operation of the electric tricycle, laying the foundation for subsequent accurate simulation and analysis.

[0029] In order to make the basic model architecture more accurately reflect the actual circuit characteristics of the target electric tricycle, it is optimized using rich historical operating parameters. The historical operating parameters contain various data of the vehicle in the past actual use process, such as the actual output power of the motor under different road conditions, current conversion, actual working voltage of the controller, etc. Through in-depth analysis of these historical data, such as statistical indicators such as the average value and standard deviation of various parameters under different load working conditions, and analysis of the trend of parameters over time, this information is integrated into the basic model architecture. Using an iterative optimization algorithm, the parameter values ​​and logical relationships in the model are continuously adjusted according to the historical operating parameters, so that the output results of the model when simulating different load working conditions are more consistent with the actual historical data. After multiple iterative optimizations, a highly accurate circuit simulation model that can truly reflect the circuit characteristics of the target electric tricycle is finally determined, providing a reliable theoretical basis for subsequent welding quality monitoring and analysis.

[0030] In a possible implementation, the basic model architecture is optimized by using historical operating parameters to determine the circuit simulation model, further comprising: Based on the historical operating parameters, the load working state duration is sorted in order from long to short, and multiple historical operating parameter subsets associated with different load working states are obtained; conventional usage scenarios are formulated, and the conventional usage scenarios include startup usage scenarios, acceleration usage scenarios, constant speed driving usage scenarios, and deceleration usage scenarios; according to the conventional usage scenarios and the multiple historical operating parameter subsets associated with the different load working states, the basic model architecture is iteratively trained.

[0031] Specifically, the collected rich historical operating parameters are analyzed in depth. These historical operating parameters cover various data records of electric tricycles in actual use, including the actual output power change of the motor, the current conversion of the power conversion component, the working voltage fluctuation of the controller and other information. These historical operating parameters are sorted in order from long to short according to the duration of the load working state. For example, in long-term actual use, the vehicle may be in a uniform driving state for most of the time, which lasts the longest; the acceleration and deceleration states are relatively rare, and the start state lasts for a shorter time. Through this sorting method, the proportion and time distribution characteristics of different load working states in actual operation can be clearly identified. Based on this, the historical operating parameters are divided into multiple subsets, each of which is closely related to a specific load working state. In this way, for the uniform driving state, a historical operating parameter subset containing a large number of changes in various parameters during uniform driving can be obtained, which contains information such as the stable output power range of the motor in this state, the relatively constant current value and the stable working voltage of the controller. Similarly, for load working states such as starting, acceleration and deceleration, corresponding historical operating parameter subsets are obtained respectively, providing a targeted data basis for subsequent model optimization.

[0032] In order to enable the circuit simulation model to better simulate the various working conditions of electric tricycles in actual use, conventional usage scenarios are proposed. The startup usage scenario is the initial stage of vehicle operation. At this time, the motor needs to provide a large torque to overcome the static inertia of the vehicle, and the current demand increases instantly. The controller needs to accurately control the motor startup process to ensure smooth startup. In the acceleration usage scenario, the vehicle needs additional power to increase the speed, the motor output power increases rapidly, and the current rises accordingly. The controller adjusts the motor speed and torque according to the acceleration demand. This process involves complex power matching and power management. The uniform speed driving scenario is a common state of vehicle operation. The motor output power remains relatively stable, and the current and voltage are also at a relatively stable level. At this time, the energy consumption and performance of the vehicle are relatively stable. The deceleration usage scenario involves an energy recovery mechanism. The motor changes to a generator mode when the vehicle decelerates, converting the vehicle's kinetic energy into electrical energy and feeding it back to the battery. This process requires the controller to accurately control the energy recovery efficiency, while ensuring the smoothness and safety of the vehicle's deceleration. These conventional usage scenarios cover the main working conditions of electric tricycles in actual operation, providing a comprehensive simulation scenario framework for model optimization.

[0033] Iterative training is carried out on the basic model architecture based on the proposed conventional usage scenarios and multiple historical operating parameter subsets associated with different load working states. During the training process, each conventional usage scenario is used as a training unit, and the historical operating parameter subset of the corresponding load working state is input. For example, when training for the acceleration usage scenario, the historical operating parameter subset under the acceleration state is input into the basic model architecture. The model simulates the circuit operation during the acceleration process based on these input data, and calculates the simulation results such as motor output power, current change, and voltage fluctuation. These simulation results are then compared with the real data in the actual historical operating parameter subset, and the error is calculated. By continuously adjusting the parameters in the model, such as the equivalent resistance, inductance, and capacitance of the circuit components, and the control coefficient in the control algorithm, the error between the simulation results and the real data is reduced. After each parameter adjustment, the historical operating parameter subset is input again for simulation calculation and error evaluation, and iterative training is repeated until the simulation results of the model in each conventional usage scenario are highly consistent with the real historical data. After multiple iterations of training, the basic model architecture was gradually optimized into a high-precision circuit simulation model that can accurately simulate the circuit characteristics of electric tricycles under different usage scenarios and load working conditions, providing a reliable theoretical basis and accurate simulation tools for subsequent welding quality monitoring and analysis.

[0034] In a possible implementation, identifying a welding quality characteristic index, performing a parameter drift analysis on a connection between a motor assembly in the power unit and an electric tricycle controller according to the circuit simulation model, determining a first parameter drift set, and calibrating a first welding point potential fault queue, further comprising: Based on the circuit simulation model, a first one-way pointer pointing to the motor assembly is set through the connection between the motor assembly in the power unit and the electric tricycle controller; based on the circuit simulation model, a second one-way pointer pointing to the electric tricycle controller is set through the connection between the motor assembly in the power unit and the electric tricycle controller; based on the first one-way pointer and the second one-way pointer, multiple control loops corresponding to the circuit simulation model are traversed, and according to the first parameter drift set, the potential fault queue of the first welding point is calibrated.

[0035] Specifically, when using the circuit simulation model for fault analysis, firstly, based on the model, a one-way pointer is set for the connection between the motor assembly in the power unit and the electric tricycle controller. The first one-way pointer pointing to the motor assembly is set to accurately track the control signal and the power transmission path along the direction from the controller to the motor assembly. This pointer clarifies the direction of information flow from the controller to the motor assembly through the connection line, which helps to accurately grasp the circuit characteristics and signal transmission related to the motor assembly in subsequent analysis. Similarly, a second one-way pointer pointing to the electric tricycle controller is set, which points to the controller from one side of the motor assembly, so that the transmission path of the motor operating status feedback signal and power consumption information to the controller can be traced back. The two one-way pointers cooperate with each other to provide clear path guidance for a comprehensive analysis of the connection relationship between the motor assembly and the controller, ensuring that no key information is missed in the complex circuit structure.

[0036] With the help of the set first one-way pointer and the second one-way pointer, start traversing multiple control loops corresponding to the circuit simulation model. Starting from the motor component end pointed by the first one-way pointer, follow the direction determined by the pointer to conduct detailed exploration of each control loop in turn. During the traversal process, carefully check the key parts such as each component, line connection point and solder joint in the loop, and record its electrical parameters, signal transmission characteristics and other information. At the same time, starting from the controller end pointed by the second one-way pointer, traverse the control loop in reverse, and confirm the status of each component in the loop again. Through traversal in both positive and negative directions, a comprehensive and detailed investigation of the control loop is achieved to ensure that the most complete and accurate information about the loop is obtained, providing sufficient data support for subsequent fault judgment.

[0037] On the basis of traversing the control loop, the first welding point potential fault queue is calibrated according to the data in the first parameter drift set. The first parameter drift set contains parameter change information related to the connection between the motor assembly and the controller monitored during the actual welding process, such as the drift value of the welding point resistance, the change in current conduction at the welding point, etc. When traversing to a certain welding point, the parameters corresponding to the welding point are compared with the standard range in the first parameter drift set. If the parameters of a welding point exceed the normal drift range, for example, the drift of the welding point resistance is too large, which may cause increased power loss or unstable signal transmission, the welding point is marked as a potential fault point and added to the first welding point potential fault queue. In this way, the welding points that may cause faults due to welding quality problems in the connection part between the motor assembly and the controller can be accurately identified, which provides a clear goal for subsequent targeted detection, repair or quality improvement, effectively improves the efficiency and accuracy of fault detection, and ensures the reliability and stability of the key connection part of the electric tricycle power unit.

[0038] In a possible implementation manner, determining the first parameter drift set further includes: Add a preset welding standard, and the welding quality characteristic index meets the preset welding standard; based on the first unidirectional pointer and the second unidirectional pointer, perform a correlation analysis on the parameter drift deviation degree and the welding quality deviation degree, and formulate a first deviation function; based on the first deviation function, perform a parameter drift analysis on the connection between the motor assembly in the power unit and the electric tricycle controller, and determine the first parameter drift set.

[0039] Specifically, to ensure the accuracy and consistency of welding quality assessment, preset welding standards are first introduced. These standards cover the ideal index range of solder joint morphology, solder temperature, solder quantity, etc., and are formulated based on a large amount of experimental data and industry experience. For example, in terms of solder joint morphology, the ideal shape, size and surface flatness of the solder joint are specified to ensure good mechanical connection strength and electrical conductivity; for solder temperature, a suitable soldering temperature range is set to ensure that the solder can fully melt and infiltrate the welding part, while avoiding damage to components or excessive oxidation of solder due to excessive temperature, and problems such as cold soldering may be caused by too low temperature; the solder quantity standard specifies the optimal solder volume or weight required for each solder joint to ensure that the solder joint has sufficient conductivity and does not cause short circuit risks or unnecessary weight due to excessive solder. During the entire welding quality assessment process, the actual monitored welding quality characteristic indicators are strictly compared with these preset welding standards, which serve as an important basis for judging whether the welding quality is qualified and the degree of deviation.

[0040] Based on the first unidirectional pointer pointing to the motor assembly and the second unidirectional pointer pointing to the electric tricycle controller, the correlation analysis of the deviation degree of parameter drift and the deviation degree of welding quality is carried out, and then the first deviation function is formulated. Through the first unidirectional pointer, the changes of the parameters related to the signal and power transmission path from the controller to the motor assembly can be accurately tracked, such as the drift of parameters such as solder joint resistance and inductance along the path as the welding quality changes; using the second unidirectional pointer, the feedback signal of the motor assembly operation status and the parameter fluctuation caused by welding problems during the transmission of information such as power consumption to the controller can be obtained in reverse. Considering the parameter changes on these forward and reverse paths, they are compared with the preset welding standards, and the degree of deviation of parameter drift from the standard value and the degree of deviation of welding quality from the ideal state caused by the drift are analyzed. For example, excessive drift of solder joint resistance may lead to increased power transmission loss, thereby affecting the power output of the motor, which reflects the close relationship between parameter drift and welding quality. Through the analysis and mathematical modeling of a large amount of actual data, a first deviation function that can accurately describe this correlation is developed. This function usually contains mathematical expressions of variables such as parameter drift, the difference between welding quality characteristic indicators and preset standards, and their mutual relationships, providing a quantitative tool for subsequent precise analysis of parameter drift.

[0041] With the proposed first deviation function, an in-depth parameter drift analysis is conducted on the connection between the motor assembly in the power unit and the electric tricycle controller to determine the first parameter drift set. The parameter values ​​of the connection parts actually monitored are substituted into the first deviation function to calculate the drift degree of each parameter and the overall parameter drift. For example, for key parameters such as solder joint resistance, inductance, and capacitance, the drift ratio or specific numerical change relative to the preset standard value under the current welding state is calculated according to the function. These calculated parameter drift data are sorted and summarized to form the first parameter drift set. This set comprehensively and accurately reflects the parameter changes caused by welding quality problems in the connection part between the motor assembly and the controller, which provides key data support for further judging whether the welding quality is qualified, calibrating potential fault points, and taking corresponding improvement measures, which helps to ensure the stable operation and performance of the electric tricycle power system.

[0042] In a possible implementation manner, formulating the first deviation function further includes: Define the degree of parameter drift deviation , welding quality deviation degree ; Correlation analysis is performed on the degree of parameter drift deviation and welding quality deviation. The first deviation function ;in, represents the parameter drift and its mean ( ) and standard deviation ( ) reflects the relative size of parameter drift. is an exponential decay term, where α is a positive coefficient, is the hyperbolic tangent function term corresponding to the welding quality deviation, γ, Used to adjust the hyperbolic tangent function term.

[0043] Specifically, in the welding quality monitoring system of the electric tricycle controller circuit board, the parameter drift deviation degree is defined Degree of deviation from welding quality These two important concepts are used to accurately quantify the changes in relevant parameters during the welding process and the degree of deviation of welding quality from the ideal state. By calculating the parameter drift and its mean and standard deviation The absolute value of the ratio This absolute value can clearly reflect the relative size of the parameter drift relative to its normal distribution range, thereby intuitively showing the degree of parameter change. For example, if the calculated value of the parameter drift deviation of a solder joint resistance is large, it means that the actual value of the resistance is significantly different from the mean and standard deviation under normal circumstances, which may indicate that there are factors that affect the resistance performance of the solder joint during the welding process, such as unstable welding temperature causing changes in the metal structure that affect the resistance value. At the same time, the exponential decay term (in is a positive coefficient) is introduced, which can reflect the attenuation trend of the overall impact as the parameter drift deviation increases. When the parameter drift is small, this term has a greater impact on the function value, and as the drift increases, its impact gradually weakens, which helps to reasonably consider the influence weight of different degrees of parameter drift on the system in the model. In addition, the hyperbolic tangent function term corresponding to the welding quality deviation (in The function term used to adjust the function is also taken into consideration. The characteristics of the hyperbolic tangent function enable it to take values ​​between -1 and 1, which can well reflect the variation of the welding quality deviation within a certain range. Moreover, the adjustment can more accurately fit the deviation relationship between the actual welding quality and the ideal state. The first deviation function finally constructed , combining the above factors, through the degree of parameter drift deviation Degree of deviation from welding quality And the correlation coefficient , , The synergistic effect of can accurately evaluate the welding quality status of the connection part between the motor assembly and the electric tricycle controller. This function provides an important calculation basis for the subsequent determination of the first parameter drift set, so that the system can obtain accurate parameter drift analysis results based on actual monitoring data by substituting it into the function calculation, thereby more effectively identifying potential welding quality problems, ensuring the welding quality of the electric tricycle controller circuit board, and improving the performance and reliability of the entire vehicle.

[0044] In a possible implementation manner, formulating the first deviation function further includes: A welding standard update strategy is set based on a first deviation function corresponding to the first parameter drift set and a second deviation function corresponding to the second parameter drift set; and an update decision is made on the preset welding standard through the welding standard update strategy.

[0045] Specifically, the first deviation function corresponding to the first parameter drift set and the second deviation function corresponding to the second parameter drift set are analyzed in depth. It reflects the parameter drift and welding quality deviation of the connection part between the motor assembly in the power unit and the electric tricycle controller. is the parameter drift deviation degree of the connection part, is the degree of deviation of welding quality, , , , , is the correlation coefficient. The second deviation function ( , its form is similar to Similarly, the parameters corresponding to the connection between the power conversion component and the controller) reflect the relevant conditions of the connection between the power conversion component and the controller. Through the comprehensive study of these two deviation functions, the welding standard update strategy is set. For example, if in a certain number of welding samples, the first deviation function The calculation results of frequently exceed the preset threshold range, indicating that the welding quality stability of the connection between the motor component and the controller is poor, and the relevant standards for this part of the welding need to be adjusted. At this time, the strategy may stipulate further analysis and Related parameter drift and welding quality deviation factors, such as whether the standards of solder joint shape, solder temperature, solder quantity, etc. need to be optimized. For the second deviation function A similar analysis method is also used. If It shows that there are many potential problems in the connection between the power conversion component and the controller, and the evaluation process of the welding standards for this part has also been initiated.

[0046] When it is determined that the preset welding standard needs to be updated according to the welding standard update strategy, the update decision is implemented. If it is found that the parameter drift of a certain type of weld point is generally large in the actual welding process, the first deviation function or the second deviation function If the deviation degree of parameter drift in the function is significantly affected, it is decided to adjust the morphological standard of this type of solder joint, such as increasing the solder joint area or improving the solder joint roundness standard to enhance the connection reliability of the solder joint. At the same time, if the degree of welding quality deviation is obvious in terms of temperature, such as solder temperature fluctuation leading to unstable welding quality, which in turn affects the calculation results of the deviation function, the solder temperature standard may be updated to optimize the welding temperature range. In the update decision process, the relationship between different deviation functions and their combined impact on the overall welding quality are also considered. For example, if and At the same time, abnormalities occur in certain parameters, and multiple related welding standards need to be coordinated and adjusted to ensure that the connections between motor components, power conversion components and controllers can meet higher quality requirements. Through this welding standard update strategy and decision implementation process based on deviation function analysis, the preset welding standards can be continuously optimized to make them more in line with actual welding conditions, improve the welding quality of the electric tricycle controller circuit board, and ensure the performance and reliability of the electric tricycle.

[0047] In a possible implementation method, establishing a welding quality assessment model also includes: According to the warranty period of the target electric tricycle, the welding failure mode and time distribution are identified by comparing with the welding quality assessment model; and the welding standard update strategy is adjusted according to the welding failure mode and time distribution.

[0048] Specifically, the warranty period of the target electric tricycle is an important time window that reflects product quality and reliability. During this period, the use of the vehicle and possible problems can provide valuable feedback for welding quality assessment. By combining the warranty period with the welding quality assessment model, the relationship between welding quality and long-term vehicle performance is deeply explored. For example, in the early warranty period, the focus is on the impact of the initial stability of the welding point on the vehicle's starting, acceleration and other performance; in the middle of the warranty period, the analysis is on how the welding quality affects the power output stability and power conversion efficiency of the vehicle during continuous operation; at the end of the warranty period, the focus is on the role of aging and potential failure of the welding point on the overall performance degradation of the vehicle. The welding quality assessment model is constructed based on the first parameter drift set and the first welding point potential fault queue, the second parameter drift set and the second welding point potential fault queue, which can accurately predict and evaluate the impact of welding quality on the operation of the electric tricycle controller. During the warranty period, according to various problems that occur in the actual operation of the vehicle, such as abnormal motor control and reduced power conversion efficiency, the welding quality assessment model is compared to determine whether these problems are related to the welding failure mode. For example, if the motor speed is frequently unstable during the warranty period, the evaluation model can be used to analyze whether it is caused by parameter drift or potential failure at the welding point where the motor assembly is connected to the controller, thereby identifying possible welding failure modes. With the help of vehicle failure data and welding quality monitoring data collected during the warranty period, the welding failure mode and time distribution are identified in detail. Welding failure modes include various forms such as solder cracking, cold solder joints, and solder corrosion. By statistically analyzing welding failure cases that occur in different time periods, the probability of occurrence and time node distribution of each failure mode during the warranty period are determined. For example, it is found that the incidence of solder cracking is higher at the end of the warranty period, which is due to long-term vibration and temperature cycles causing solder fatigue; while cold solder joints occur in a certain proportion at the beginning of the warranty period, which may be due to improper initial adjustment of the welding process. At the same time, the relationship between welding failure modes and vehicle operating conditions and environmental factors is analyzed. Under different driving conditions (such as bumpy roads, flat roads) and use environments (such as humid environments, high temperature environments), the changing laws of welding failure modes are observed. For example, in a humid environment, the corrosion rate of the weld may accelerate, causing weld failure to occur early; under driving conditions with frequent acceleration and deceleration, the stress on the weld changes greatly, which can easily cause weld cracking and other problems. Based on these analysis results, a detailed chart of the weld failure mode and time distribution is drawn to provide intuitive data support for subsequent strategy adjustments.

[0049] According to the identified welding failure modes and time distribution, the welding standard update strategy is adjusted in a targeted manner. If it is found that solder joint cracking becomes the main failure mode at the end of the warranty period and is related to long-term vibration and temperature cycling, then in the update strategy, the requirements for the mechanical strength and fatigue resistance of the solder joints are strengthened. For example, the solder joint morphology standard is adjusted, the thickness or area of ​​the solder joint is increased to improve the ability of the solder joint to withstand vibration and temperature stress; the solder composition standard is optimized, and solder materials that are more suitable for long-term stability are selected. For the problem of cold solder joints that occurs more frequently in the early warranty period, the focus is on improving the welding process standards, such as strictly controlling the welding temperature and time, strengthening the training of welding workers' operating skills, and ensuring that each solder joint can achieve good welding quality. At the same time, according to the impact of different environmental factors on welding failure, environmental adaptability welding standards are formulated. In a humid environment, the moisture resistance performance standards of the solder joints are improved, such as adding moisture-proof coatings or improving the packaging process; in a high temperature environment, the solder temperature standard is optimized to ensure the stability of the solder at high temperatures during the welding process, and prevent the solder performance from deteriorating due to excessively high temperatures, which may cause welding failure. Through this adjustment of the welding standard update strategy based on warranty period feedback, the welding quality can be continuously improved, the service life of the electric tricycle controller can be extended, and the reliability and durability of the entire vehicle can be improved.

[0050] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0051] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0052] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. Electric tricycle controller circuit board welding quality monitoring system, characterized in that: include: A power unit connection module, the power unit connection module is used to connect the power unit of the target electric tricycle, the power unit includes a motor assembly, a power conversion assembly, and an electric tricycle controller; A circuit simulation model building module, wherein the circuit simulation model building module builds a circuit simulation model based on a target electric tricycle, wherein the circuit simulation model includes a plurality of control loops and marks a plurality of welding points on each control loop; A welding monitoring unit adopts a module, wherein the welding monitoring unit adopts a welding monitoring unit, performs welding synchronization monitoring on each control loop, and collects a monitoring data set, wherein the monitoring data set includes a solder point morphology subset, a solder temperature subset, and a solder quantum subset, and the welding monitoring unit is deployed on a welding workbench; A first parameter drift set determination module, the first parameter drift set determination module is used to parse the solder point morphology subset, the solder temperature subset, and the solder quantum set, identify welding quality characteristic indicators, perform parameter drift analysis on the connection between the motor assembly in the power unit and the electric tricycle controller according to the circuit simulation model, determine the first parameter drift set, and calibrate the first welding point potential fault queue; A second parameter drift set acquisition module, which performs parameter drift analysis on the connection between the power conversion component in the power unit and the electric tricycle controller based on the welding quality characteristic index and the circuit simulation model, acquires a second parameter drift set, and calibrates a potential fault queue of a second welding point; A welding quality assessment model establishment module, which establishes a welding quality assessment model based on the first parameter drift set and the first welding point potential fault queue, the second parameter drift set and the second welding point potential fault queue. The welding quality assessment model is used to monitor and remind the electric tricycle controller of welding quality.

2. The electric tricycle controller circuit board welding quality monitoring system according to claim 1, characterized in that: Based on the target electric tricycle, a circuit simulation model is established, including: Obtaining basic model parameters of the target electric tricycle, the basic model parameters including the rated output power and speed range of the motor assembly, the rated conversion current and current capacity of the power conversion assembly, and the rated control voltage and voltage range of the electric tricycle controller; Establishing a basic model framework identified by the basic model parameters, wherein the basic model framework includes different load working states; The basic model architecture is optimized through historical operating parameters to determine the circuit simulation model.

3. The electric tricycle controller circuit board welding quality monitoring system as claimed in claim 2, characterized in that: The basic model architecture is optimized by using historical operating parameters to determine the circuit simulation model, including: Based on the historical operating parameters, the load working state duration is sorted in descending order to obtain a plurality of historical operating parameter subsets associated with different load working states; Formulate regular usage scenarios, including startup usage scenarios, acceleration usage scenarios, constant speed driving usage scenarios, and deceleration usage scenarios; The basic model architecture is iteratively trained according to the conventional usage scenarios and multiple historical operating parameter subsets associated with the different load working states.

4. The electric tricycle controller circuit board welding quality monitoring system as claimed in claim 3, characterized in that: Identifying welding quality characteristic indicators, performing parameter drift analysis on the connection between the motor assembly in the power unit and the electric tricycle controller according to the circuit simulation model, determining a first parameter drift set, and calibrating a first welding point potential fault queue, including: Based on the circuit simulation model, a first one-way pointer pointing to the motor assembly is set through the connection between the motor assembly in the power unit and the electric tricycle controller; Based on the circuit simulation model, a second one-way pointer pointing to the electric tricycle controller is set through the connection between the motor assembly in the power unit and the electric tricycle controller; Based on the first one-way pointer and the second one-way pointer, multiple control loops corresponding to the circuit simulation model are traversed, and according to the first parameter drift set, a first welding point potential fault queue is calibrated.

5. The electric tricycle controller circuit board welding quality monitoring system as claimed in claim 4, characterized in that: include: Adding a preset welding standard, wherein the welding quality characteristic index complies with the preset welding standard; Based on the first one-way pointer and the second one-way pointer, a correlation analysis is performed on the deviation degree of parameter drift and the deviation degree of welding quality, and a first deviation function is formulated; Based on the first deviation function, a parameter drift analysis is performed on the connection between the motor assembly in the power unit and the electric tricycle controller to determine a first parameter drift set.

6. The electric tricycle controller circuit board welding quality monitoring system as claimed in claim 5, characterized in that: Define the degree of parameter drift deviation , welding quality deviation degree ; The correlation analysis between the parameter drift deviation degree and the welding quality deviation degree is carried out. The first deviation function ; in, represents the parameter drift and its mean ( ) and standard deviation ( ) reflects the relative size of parameter drift. is an exponential decay term, where α is a positive coefficient, is the hyperbolic tangent function term corresponding to the welding quality deviation, γ, Used to adjust the hyperbolic tangent function term.

7. The electric tricycle controller circuit board welding quality monitoring system as claimed in claim 6, characterized in that: Setting a welding standard update strategy based on a first deviation function corresponding to the first parameter drift set and a second deviation function corresponding to the second parameter drift set; Through the welding standard update strategy, an update decision is made on the preset welding standard.

8. The electric tricycle controller circuit board welding quality monitoring system as claimed in claim 7, characterized in that: Establish a welding quality assessment model, including: According to the warranty period of the target electric tricycle, comparing the welding quality assessment model, identifying the welding failure mode and time distribution; The welding standard update strategy is adjusted according to the welding failure mode and time distribution.

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