Seat test method and test system combining high and low temperature environment chamber and robot

Abstract

The invention relates to the technical field of material and structure testing, in particular to a seat testing method and system combining a high and low temperature environment chamber and a robot, and the method comprises the steps: controlling the robot to execute a non-contact approaching action and a contact testing action, and collecting the joint operation data of the robot; according to joint operation data in a non-contact approaching action stage, a viscous resistance coefficient sequence is determined, and an internal friction power threshold model changing along with accumulated shearing duration is constructed; determining a current internal friction power threshold value according to the internal friction power threshold value model, the current accumulated shearing duration and the current joint rotating speed in the stage that the robot executes the contact test action; determining external contact power according to the joint operation data in the contact test action stage and the current internal friction power threshold; and determining a seat reaction force according to the external contact power, and controlling the robot to test the seat based on the seat reaction force. According to the invention, the seat can be accurately and reliably tested under a harsh temperature condition.

Description

Technical Field

[0001] This invention relates to the field of materials and structural testing technology, specifically to a seat testing method and system that combines a high and low temperature environment chamber and a robot. Background Technology

[0002] In the durability and reliability testing of automotive seats, to evaluate the performance of their materials and structures under extreme climatic conditions, it is typically necessary to use industrial robots to simulate the sitting and getting in / out movements of a real human body in a high- or low-temperature environment chamber. This testing method requires the robot to apply precise and gentle contact forces to the seat in order to obtain effective test data and avoid damaging the brittle seat materials.

[0003] Currently, to achieve this type of contact force control, the industry typically relies on installing a six-dimensional force sensor at the robot's end effector or employing a sensorless force control scheme based on internal robot current feedback. However, when testing is conducted in extremely low-temperature environments (e.g., -30°C and below), the grease inside the robot's joints solidifies due to the low temperature, causing significant changes in its rheological properties. This results in joint running resistance exhibiting significant amplitude fluctuations over time. Existing force control methods struggle to reliably and stably extract the weak force signals generated by seat contact under such highly disturbed and time-varying internal resistance conditions, severely impacting the accuracy, safety, and reliability of the testing process. Summary of the Invention

[0004] To address the technical problem of insufficient accuracy in detecting and controlling seat contact force caused by changes in the rheological properties of robot joint lubricating grease in low-temperature environments, the present invention aims to provide a seat testing method and system that combines a high-low temperature environment chamber and a robot. The specific technical solution adopted is as follows: Firstly, a method for testing a seat combining a high- and low-temperature environmental chamber and a robot is provided. This method includes: controlling the robot to sequentially execute non-contact approaching actions and contact testing actions, and continuously collecting joint operation data of the robot, including drive current, joint rotation speed, and joint angular acceleration; determining a viscous drag coefficient sequence reflecting the rheological properties of the lubricating grease within the joint based on the joint operation data collected during the non-contact approaching action phase, and constructing an internal power dissipation threshold model that varies with cumulative shear duration based on the viscous drag coefficient sequence, where cumulative shear duration characterizes the total duration of shear action on the lubricating grease; determining a current internal power dissipation threshold based on the internal power dissipation threshold model, the current cumulative shear duration, and the current joint rotation speed during the contact testing action phase; determining an external contact power based on the joint operation data collected during the contact testing action phase and the current internal power dissipation threshold; determining the seat reaction force based on the external contact power, and controlling the robot to test the seat based on the seat reaction force.

[0005] In one possible design, the robot is controlled to sequentially execute a non-contact approach action and a contact test action, while continuously collecting joint operation data of the robot. This includes: controlling the robot to first execute a non-contact approach action and simultaneously starting a timer to obtain the cumulative shearing time; after the robot's end effector moves to a preset position above the seat, controlling the robot to execute a contact test action; during the execution of the non-contact approach action and the contact test action, the joint operation data of the robot's main load-bearing joint is collected synchronously at a fixed control cycle. The main load-bearing joint is the joint that undertakes the main driving task in the seat indentation test and whose movement contributes the most to the displacement of the robot's end effector in the direction of gravity.

[0006] In one possible design, based on joint operation data collected during the non-contact approach phase, a sequence of viscous resistance coefficients reflecting the rheological properties of the grease within the joint is determined. This includes: for each sampling moment during the non-contact approach phase, based on preset gravity compensation conditions, and according to the driving current and joint angular acceleration collected at the sampling moment, determining the net grease resistance torque corresponding to the sampling moment, where the net grease resistance torque is the net resistance generated by the grease; determining the viscous resistance coefficient corresponding to the sampling moment based on the joint rotational speed and the net grease resistance torque at the sampling moment, where the viscous resistance coefficient reflects the viscosity characteristics of the grease; and removing viscous resistance coefficients whose absolute joint rotational speed is lower than a preset rotational speed threshold from multiple sampling moments to obtain the viscous resistance coefficient sequence.

[0007] In one possible design, an internal friction power threshold model is constructed based on the viscous resistance coefficient sequence, which varies with the cumulative shear time. This includes: fitting a function to the viscous resistance coefficient sequence to obtain a resistance attenuation benchmark function, which reflects the attenuation law of the macroscopic resistance of the grease with the shear time; determining the residuals of each data point in the viscous resistance coefficient sequence relative to the resistance attenuation benchmark function; using the attenuation rate parameter included in the resistance attenuation benchmark function as a constraint, performing upper envelope fitting on the residuals to obtain an upper bound function for resistance fluctuation, which defines the maximum statistical fluctuation range of the resistance; and constructing an internal friction power threshold model based on the resistance attenuation benchmark function and the upper bound function for resistance fluctuation.

[0008] In one possible design, a function fitting is performed on the viscous drag coefficient sequence to obtain a drag attenuation benchmark function, including: constructing an exponential decay function model, which includes a first parameter characterizing steady-state impedance, a second parameter characterizing the magnitude of change, and a third parameter characterizing the viscosity attenuation rate; determining the initial value of the first parameter based on the statistical characteristics of data located at the end of the viscous drag coefficient sequence and accounting for a first preset proportion; determining the initial value of the second parameter based on the statistical characteristics of data located at the beginning of the viscous drag coefficient sequence and accounting for a second preset proportion, and the initial value of the first parameter; setting an initial value for the third parameter; and using the initial values ​​of the first, second, and third parameters as the starting point for iteration, fitting the exponential decay function model through a nonlinear optimization algorithm to determine the drag attenuation benchmark function.

[0009] In one possible design, the current internal power threshold is determined based on the internal power threshold model, the current cumulative shear duration, and the current joint rotation speed. This includes: inputting the current cumulative shear duration into the internal power threshold model; obtaining a reference resistance value based on the current cumulative shear duration using the resistance attenuation reference function included in the internal power threshold model; obtaining a fluctuation upper bound value based on the current cumulative shear duration using the resistance fluctuation upper bound function included in the internal power threshold model; and obtaining the current internal power threshold based on the reference resistance value, the fluctuation upper bound value, and the current joint rotation speed.

[0010] In one possible design, the external contact power is determined based on the joint operation data collected during the contact test phase and the current internal power consumption threshold. This includes: determining the current net output torque based on the current drive current and the current joint angular acceleration according to preset gravity compensation conditions; determining the total drive power currently output by the motor based on the current net output torque and the current joint speed; and determining the external contact power based on the total drive power and the current internal power consumption threshold.

[0011] In one possible design, the seat reaction force is determined based on the external contact power, and the robot is controlled to test the seat based on the seat reaction force. This includes: obtaining the seat reaction force based on the external contact power and the linear velocity of the robot end effector along the seat pressing direction; calculating the position correction amount of the robot end effector through an admittance control algorithm based on the deviation between the seat reaction force and the preset target load; and generating motion control commands for the robot based on the position correction amount.

[0012] In one possible design, the above-mentioned seat testing method combining high and low temperature environment chambers and robots further includes: controlling the robot to exit the test when the seat reaction force determined at multiple consecutive moments is within the allowable error range of the preset target load, or when the robot end effector's indentation depth relative to the seat reaches the preset travel limit.

[0013] Secondly, a seat testing system combining a high- and low-temperature environmental chamber and a robot is provided, comprising: a data acquisition unit for controlling the robot to sequentially execute non-contact approach actions and contact test actions, and continuously acquiring joint operation data of the robot, including drive current, joint rotation speed, and joint angular acceleration; a model building unit for determining a viscous drag coefficient sequence reflecting the rheological properties of the lubricating grease within the joint based on the joint operation data acquired during the non-contact approach action phase, and constructing an internal power threshold model that varies with the cumulative shear time based on the viscous drag coefficient sequence; an internal power threshold determination unit for determining the current internal power threshold based on the internal power threshold model, the current cumulative shear time, and the current joint rotation speed during the contact test action phase; a power determination unit for determining the external contact power based on the joint operation data acquired during the contact test action phase and the current internal power threshold; and a control unit for determining the seat reaction force based on the external contact power and controlling the robot to test the seat based on the seat reaction force.

[0014] The present invention has the following beneficial effects: In the seat testing method combining high and low temperature environment chamber and robot provided by this invention, there is no need to rely on external force sensors that are prone to failure in low temperature environment. The accurate detection and control of seat contact force can be achieved solely through joint operation data collected by the robot itself, which greatly reduces testing costs and maintenance difficulty. By constructing an internal power threshold model that dynamically changes with the cumulative shearing time through data analysis of the non-contact approach action stage, it is adapted to the rheological characteristics of joint grease resistance decay and fluctuation convergence in low temperature environment, and completely solves the problem that the traditional fixed threshold method cannot take into account both the anti-interference capability in the early stage of testing and the sensitivity of weak contact signal detection in the later stage. Meanwhile, from the timing synchronization of data acquisition and the purification of viscous drag coefficient, to the precise separation of external contact power and the real-time inverse solution of seat reaction force, and then to the adjustment of robot motion based on admittance control, the entire process is progressive and logically closed-loop, effectively eliminating the interference of irrelevant factors such as gravity, inertia, and speed changes, ensuring the purity of contact force detection and the smoothness of control. This not only avoids damage to the brittle seat material due to rigid control at low temperatures, but also significantly improves the force control accuracy, data reliability, and test stability of seat durability testing under extreme temperature conditions, fully meeting the industry's stringent requirements for seat performance testing under extreme climatic conditions. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of a seat testing system combining a high and low temperature environment chamber and a robot, provided in one embodiment of the present invention. Figure 2 This is a schematic flowchart of a seat testing method combining a high and low temperature environment chamber and a robot, provided as an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a seat testing method and system combining a high- and low-temperature environment chamber and a robot proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] In embodiments of the present invention, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in embodiments of the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0019] In the description of this invention, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, "at least one" and "more than one" refer to two or more. The terms "first," "second," etc., do not limit the quantity or order of execution, and "first," "second," etc., do not necessarily imply differences.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] The following description, in conjunction with the accompanying drawings, details a specific scheme for a seat testing method and system combining a high and low temperature environment chamber and a robot provided by the present invention.

[0022] Please see Figure 1 It shows a structural schematic diagram of a seat testing system combining a high and low temperature environment chamber and a robot according to an embodiment of the present invention, such as... Figure 1 As shown, the seat testing system 10, which combines a high and low temperature environment chamber and a robot, includes a data acquisition unit 11, a model building unit 12, an internal friction threshold determination unit 13, a power determination unit 14, and a control unit 15.

[0023] The data acquisition unit 11 is used to control the robot to perform non-contact approach action and contact test action in sequence, and to continuously collect the robot's joint operation data, including drive current, joint speed and joint angular acceleration.

[0024] The data acquisition unit 11 includes an action control module, a timing management module, and a data synchronization acquisition module.

[0025] The motion control module is specifically used to control the robot to execute non-contact approach motion and contact test motion sequentially, while strictly constraining the continuity of the two motions. This ensures that after the non-contact approach motion is completed, the robot seamlessly switches to the contact test motion within a preset time threshold (e.g., 2 seconds), preventing the thixotropic re-condensation of the lubricating grease in the joints due to prolonged pauses and ensuring the validity of the rheological characteristic data. Among these, the module focuses on driving the robot's main load-bearing joints (i.e., the joints that bear the main driving task in the seat indentation test and whose motion contributes the most to the displacement of the robot's end effector in the direction of gravity) to complete the motion execution.

[0026] The timing management module is specifically used to start continuous timing to generate cumulative shearing duration, with the moment when the robot begins to perform non-contact approach actions as the zero point. This duration is monotonically accumulated throughout the entire cycle and is not reset, and is used to accurately characterize the total duration of shearing action on the grease.

[0027] The data synchronization acquisition module is specifically used to synchronously acquire the joint operation data of the robot's main load-bearing joints at a fixed control cycle (e.g., 1ms, corresponding to a 1kHz frequency), including drive current, joint speed, and joint angular acceleration. The drive current is used to characterize the drive output state of the motor, the joint speed is used to reflect the speed of joint rotation, and the joint angular acceleration is used to reflect the rate of change of the joint speed. During the acquisition process, the gravity bias component in the drive current is pre-removed to ensure data purity.

[0028] The model building unit 12 is used to determine the viscous resistance coefficient sequence reflecting the rheological properties of the grease in the joint based on the joint running data collected during the non-contact approach phase, and to build an internal power threshold model that varies with the cumulative shear time based on the viscous resistance coefficient sequence.

[0029] The model building unit 12 includes a rheological property extraction module, a function fitting module, and a model parameter freezing module.

[0030] The rheological property extraction module is specifically used to first, based on preset gravity compensation conditions (the robot controller integrates a gravity compensation algorithm at the bottom layer, or the test motion planning is executed in the horizontal plane), subtract the effects of inertia and gravity from the joint operation data during the non-contact approach phase, treat the equivalent rotational inertia of the robot in the approach posture as a constant, and calculate the net grease resistance torque (net resistance generated only by lubricating grease) by combining the drive current and joint angular acceleration; then, based on the net grease resistance torque and joint speed, generate a normalized viscous drag coefficient (specifically, the maximum and minimum value normalization method can be used to isolate the influence of speed change on resistance and simply reflect the viscosity characteristics of lubricating grease); finally, set a preset speed threshold, and remove invalid viscous drag coefficients with an absolute value of joint speed below the threshold to obtain a pure viscous drag coefficient sequence.

[0031] The function fitting module is specifically used to perform nonlinear optimization fitting on the viscous resistance coefficient sequence, construct an exponential decay function model, and determine the resistance decay benchmark function (containing a first parameter representing steady-state impedance, a second parameter representing the magnitude of change, and a third parameter representing the viscosity decay rate) that characterizes the decrease in macroscopic resistance of the lubricating grease with shear time. Then, the residuals of each data point in the viscous resistance coefficient sequence relative to the resistance decay benchmark function are calculated. Using the decay rate parameter of the resistance decay benchmark function as a constraint (following the logic of common trend constraints to ensure that fluctuations are consistent with the macroscopic resistance decay trend), an upper envelope fitting is performed on the residuals to obtain the upper bound function of resistance fluctuation, which defines the maximum statistical fluctuation range of resistance. Finally, based on the resistance decay benchmark function and the upper bound function of resistance fluctuation, the internal power threshold model is obtained.

[0032] The model parameter freezing module is specifically used to package the drag attenuation benchmark function, the drag fluctuation upper bound function, and various parameters obtained by fitting into a complete parameter set, store it in the shared memory of the seat testing system that combines the high and low temperature environment chamber and the robot, and perform a freezing operation to avoid external contact force signals from contaminating the model parameters during the contact testing phase, and to ensure the independence and purity of the model benchmark.

[0033] The internal friction threshold determination unit 13 is used to determine the current internal friction power threshold based on the internal friction power threshold model, the current cumulative shearing duration, and the current joint rotation speed during the robot's contact test action phase.

[0034] The internal friction threshold determination unit 13 is specifically used to input the real-time updated current cumulative shearing time into two functions (resistance attenuation benchmark function and resistance fluctuation upper bound function) contained in the internal friction power threshold model to obtain the benchmark resistance value (lubricating grease macroscopic resistance benchmark) and fluctuation upper limit value (resistance maximum fluctuation range) at the corresponding time. Combined with the robot's current joint speed, a preset safety factor (covering unmodeled random disturbances) is introduced, and the current internal friction power threshold is obtained through integrated calculation. This internal friction power threshold represents the maximum power upper limit required for the motor to overcome the internal lubricating grease resistance when there is no external contact.

[0035] The power determination unit 14 is used to determine the external contact power based on the joint operation data collected during the contact test action phase and the current internal power threshold.

[0036] The power determination unit 14 is specifically used to receive the current drive current, current joint angular acceleration, and current joint speed collected in real time by the data acquisition unit 11 during the contact test phase. Based on preset gravity compensation conditions, it calculates the current net output torque after deducting the influence of inertia. Then, through the integration calculation of the current net output torque and the current joint speed, it obtains the current total drive power output by the motor (including the internal power loss to overcome the resistance of the lubricating grease and the contact power to do work on the seat). The obtained total drive power is further differentially calculated with the current internal power loss threshold. When the total drive power does not exceed the current internal power loss threshold, it is determined that there is no effective contact and the external contact power is zero. When the total drive power exceeds the threshold, the excess part is the effective contact power of the motor to do work on the seat.

[0037] The control unit 15 is used to determine the seat reaction force based on the external contact power and control the robot to test the seat based on the seat reaction force.

[0038] The control unit 15 is specifically used to obtain the linear velocity of the end effector along the seat pressing direction through the robot's forward kinematics calculation. Combined with the external contact power transmitted by the power determination unit 14, a non-zero protection constant is introduced (to avoid calculation divergence when the velocity is zero). The seat reaction force is obtained through inverse kinematics of energy conservation logic. This seat reaction force directly reflects the magnitude of the contact pressure exerted by the seat on the robot's end effector. The seat reaction force obtained by inverse kinematics is then compared with a preset target load to calculate the deviation between the two. Based on a preset mass-damping-spring model, the force deviation is converted into a position correction amount for the robot's end effector through an admittance control algorithm. Motion control commands are generated according to the position correction amount to drive the robot's main load-bearing joints to adjust the end effector pressing depth, thereby achieving force-position hybrid compliant control.

[0039] The control unit 15 is also used to monitor the output seat reaction force and the depth of the robot end relative to the seat in real time. When the seat reaction force is within the allowable error range of the preset target load for multiple consecutive moments, or when the depth of the indentation reaches the preset travel limit, a test termination command is generated to control the robot to exit the test. At the same time, the timing management module of the data acquisition unit 11 is triggered to reset the timing, in order to prepare for the remodeling and data acquisition of the next round of testing.

[0040] Please see Figure 2 The diagram illustrates a flowchart of a seat testing method combining a high and low temperature environment chamber and a robot, provided by an embodiment of the present invention, including the following steps S201-S205.

[0041] S201. Control the robot to sequentially execute non-contact approach actions and contact test actions, and continuously collect joint operation data of the robot.

[0042] The joint operation data includes drive current, joint rotation speed, and joint angular acceleration.

[0043] As one possible implementation, firstly, the robot initiates a non-contact approach movement according to a preset trajectory. This movement is planned to move from the robot's initial standby position to a preset position above the seat. During this movement, the robot's end effector does not make any physical contact with the seat; it merely serves as a positional preparation for subsequent contact testing. At the instant the robot controller issues the non-contact approach movement initiation command, a built-in timer is simultaneously started to generate the cumulative shearing duration, denoted as [missing information]. Cumulative cutting time The duration of shear stress on the grease within the robot joint is used to characterize the total duration of this stress. It is monotonically accumulated throughout the subsequent non-contact approach and contact test actions without any form of reset.

[0044] Furthermore, when the robot end effector moves to the preset position above the seat, it immediately switches to the contact test action, and strictly constrains the continuity of the two actions (after the non-contact approach action is completed, the contact test action must be seamlessly started within the preset time threshold, or the two actions must maintain continuous non-zero speed movement), to avoid the thixotropic re-condensation of the lubricating grease in the joint due to long-term pause, and to ensure that the rheological state of the lubricating grease can be continuously maintained in the two action stages, providing a coherent physical state basis for subsequent rheological property analysis.

[0045] Throughout the robot's execution of non-contact approach and contact test actions, joint operation data of the robot's main load-bearing joints are synchronously collected at a fixed control cycle (e.g., 1ms, corresponding to a 1kHz sampling frequency). The main load-bearing joint is the joint that undertakes the main driving task in the seat indentation test and whose movement contributes the most to the displacement of the robot's end effector in the direction of gravity (e.g., the robot's vertical lifting axis joint). For multi-joint serial robots, this invention focuses on the main load-bearing joint, or maps the joint data to the end effector's Cartesian space for equivalent processing using a Jacobian matrix.

[0046] The collected joint operation data includes drive current. Joint rotation speed and joint angular acceleration The definitions and explanations of each parameter are as follows: Drive current This is the real-time current feedback value of the motor driver, which is the net value after deducting the gravity bias in advance. It is used to characterize the real-time drive output state of the motor and reflects the magnitude of the drive current required by the motor to overcome joint resistance, inertia and potential contact force. Joint speed The real-time rotational angular velocity of the joint is fed back by the motor encoder. It is used to characterize the speed of the joint's rotational motion. The positive and negative values ​​correspond to the direction of joint rotation, and the absolute value reflects the rotational rate. Joint angular acceleration To measure the joint rotation speed Real-time angular acceleration values ​​obtained through differential calculations or via the built-in observer are used to characterize joint rotational speeds. The rate of change reflects the acceleration or deceleration trend of joint movement.

[0047] During data acquisition, the drive current is realized through the built-in data synchronization acquisition module. Joint rotation speed and joint angular acceleration Timestamp alignment ensures strict synchronization of the three types of data at the same sampling time, including the acquired joint movement data and cumulative shearing duration. Real-time storage is performed in the shared memory of a seat testing system that combines high and low temperature environment chambers and robots.

[0048] S202. Based on the joint operation data collected during the non-contact approach phase, determine the viscous resistance coefficient sequence that reflects the rheological properties of the grease within the joint, and construct an internal power threshold model that varies with the cumulative shear time based on the viscous resistance coefficient sequence.

[0049] As one possible implementation, firstly, in the stage of determining the viscous drag coefficient sequence, based on the preset engineering decoupling premise (the robot controller has integrated a gravity compensation algorithm at its underlying level, and the collected drive current has been pre-deducted for gravity components; or the test motion plan is executed in the horizontal plane, and the projection of gravity on the main load-bearing joint axis is a constant value and has been deducted as a zero-point offset), the net grease drag torque corresponding to each sampling moment is determined based on the joint operation data collected at each sampling moment during the non-contact approach motion phase. Then, based on the joint rotation speed and net grease drag torque at the sampling moment, the viscous drag coefficient corresponding to the sampling moment is determined; and viscous drag coefficients with an absolute value of joint rotation speed lower than a preset rotation speed threshold in multiple sampling moments are eliminated to obtain the viscous drag coefficient sequence.

[0050] In some embodiments, for each sampling moment during the non-contact approach phase, based on preset gravity compensation conditions, the net grease resistance torque corresponding to the sampling moment is determined according to the driving current and joint angular acceleration collected at the sampling moment, and its formula is expressed as follows: In the formula, Sampling time The corresponding net grease drag torque is used to characterize the net resistance generated solely by the lubricating grease within the robot joints after deducting the effects of inertia and gravity. The torque constant of the motor is an inherent electromechanical conversion parameter of the motor, used to convert the drive current into the electromagnetic torque output by the motor. Sampling time The corresponding drive current, i.e. the real-time feedback value of the robot's main load-bearing joint motor driver collected during the non-contact approach phase, has had the gravity bias component pre-removed. The equivalent rotational inertia constant is given when the robot is in the non-contact approach phase. Since the seat test is a short-stroke motion with minimal changes in joint configuration, it is treated as a constant to simplify calculations and meet engineering accuracy requirements. Sampling time The corresponding joint angular acceleration, i.e. the rate of change of the angular velocity of the main load-bearing joint collected during the non-contact approach phase, is used to characterize the acceleration or deceleration trend of joint movement.

[0051] Furthermore, based on the joint rotation speed and the net grease resistance torque at the sampling time, the viscous drag coefficient corresponding to the sampling time is determined, and its formula is expressed as follows: In the formula, Sampling time The corresponding viscous resistance coefficient is a physical quantity that reflects only the viscosity characteristics of the grease itself after the effect of changes in peeling speed. It is the absolute value of the net grease resistance torque, used to eliminate the influence of the joint movement direction on the resistance sign and focus on the resistance amplitude characteristics; It represents the absolute value of the joint rotation speed, i.e., the amplitude of the rotational angular velocity of the main load-bearing joint acquired during the non-contact approach phase, used to reflect the speed of joint rotation. It is a very small positive number, and an empirical value of 0.001 can be taken to prevent the denominator from being zero.

[0052] Further data cleaning was performed on the viscous drag coefficients corresponding to the calculated sampling times to ensure data validity.

[0053] Because lubricating grease behaves as a Bingham fluid at extremely low speeds, its resistance characteristics do not conform to the aforementioned linear viscosity law. Therefore, the calculated viscous drag coefficient at this time... This can lead to a failure in physical functionality. Therefore, an effective speed threshold is set, denoted as the preset speed threshold. For example, 10% of the motor's rated speed can be taken, and the joint speed at each sampling moment during the non-contact approach action phase can be traversed. The viscous resistance coefficients corresponding to all sampling moments where the absolute value of the joint speed is lower than the preset speed threshold are eliminated. Finally, a cleaned viscous resistance coefficient sequence is obtained, which records the rheological process of the grease thinning with increasing shear time under low temperature conditions.

[0054] Secondly, in the stage of constructing the internal power threshold model, the viscous resistance coefficient sequence is fitted with a function to obtain the resistance attenuation benchmark function. This resistance attenuation benchmark function is used to reflect the attenuation law of the macroscopic resistance of the grease with the shear time.

[0055] In some embodiments, an exponential decay function model is constructed to characterize the change of the macroscopic resistance of the grease with cumulative shear time. This exponential decay function model includes a first parameter characterizing the steady-state resistance, a second parameter characterizing the magnitude of the change, and a third parameter characterizing the viscosity decay rate. The exponential decay function model can be expressed by the following formula: In the formula, Cumulative shearing time The corresponding benchmark resistance value, This represents the cumulative shearing time. The first parameter is used to characterize the basic viscosity coefficient of the grease after long-term shearing, which tends to stabilize. It can be determined based on the statistical characteristics (such as the average value) of the data located at the end of the viscous resistance coefficient sequence and accounting for a first preset proportion (such as 10%). The second parameter characterizes the decrease in resistance of the grease from its initial high viscosity state to its steady-state liquefaction state. It can be determined based on the statistical characteristics (e.g., the maximum value) of the data located at the beginning of the viscous resistance coefficient sequence and accounting for a second preset proportion (e.g., 10%) and the initial value of the first parameter (e.g., calculate the difference between the statistical characteristics of the data located at the beginning of the viscous resistance coefficient sequence and accounting for a second preset proportion, and the initial value of the first parameter; since the resistance in the initial state of the grease is necessarily greater than the resistance in the steady-state liquefaction state of the grease, this value is positive). The third parameter (also known as the grease viscosity decay rate parameter) is the reciprocal of the time constant used to characterize the rate of grease gel structure breakdown. It is a core parameter reflecting how quickly the grease thins. Empirical values ​​can be obtained by looking up a table based on the ambient chamber temperature setting (e.g., -30℃ corresponds to...). ) or set to a general positive number (such as 1); It is a natural constant.

[0056] Then, using the initial values ​​of the first, second, and third parameters as the starting point for iteration, a nonlinear optimization algorithm is used to fit the exponential decay function model to determine the drag decay benchmark function. For example, using the nonlinear least squares method, with the objective function being to minimize the mean square error between the theoretical value and the measured value of the pure viscous drag coefficient sequence, the initial values ​​of each parameter are determined in the above manner, and the exponential decay function model is fitted to obtain the drag decay benchmark function.

[0057] Furthermore, the residuals of each data point in the viscous drag coefficient sequence relative to the drag attenuation reference function are determined, and their formula is expressed as follows: , The th in the viscous drag coefficient sequence The absolute residual of each data point relative to the resistance attenuation benchmark function is used to quantify the degree to which the measured viscous resistance coefficient deviates from the macroscopic attenuation benchmark at each sampling time, i.e. the random fluctuation amplitude of the grease resistance. The th in the viscous drag coefficient sequence The viscous drag coefficient value for each data point The th in the viscous drag coefficient sequence The cumulative shearing time corresponding to each data point Based on the viscous drag coefficient sequence, the first... The cumulative shearing time corresponding to each data point is used to determine the reference resistance value using the aforementioned resistance attenuation reference function.

[0058] Furthermore, based on the "homogeneous trend constraint" strategy, the attenuation trends of grease resistance fluctuations (noise) and macroscopic resistance (signal) originate from the same physical mechanism (destruction of the gel skeleton structure). Using the attenuation rate parameter (the third parameter in the aforementioned resistance attenuation benchmark function) included in the resistance attenuation benchmark function as a constraint, an upper envelope fitting is performed on the residuals to obtain the upper bound function of resistance fluctuation, which defines the maximum statistical fluctuation range of resistance. Its formula is expressed as follows: In the formula, Cumulative shearing time The corresponding upper limit of fluctuation, This represents the cumulative shearing time. The initial noise amplitude is used to characterize the maximum fluctuation amplitude when the grease gel aggregates are not completely broken up during the initial stage of non-contact approach action. To ensure the reusable decay rate parameter, the upper bound of the fluctuation is consistent with the decay trend of the macro resistance. This is the steady-state noise amplitude, used to characterize the basic fluctuation amplitude where resistance fluctuations tend to stabilize after the complete disintegration of the grease gel structure. It is a natural constant.

[0059] In the upper envelope fitting process, a quantile regression algorithm is used to ensure that the fitted upper bound function of the resistance fluctuation can cover the vast majority of absolute residual points, and a set of... , making The curve converges at the same decay rate on the time axis and is located above the vast majority of residual points, avoiding misjudgment of contact signals due to random fluctuations.

[0060] Finally, based on the resistance attenuation benchmark function and the resistance fluctuation upper bound function, an internal power threshold model is constructed.

[0061] In some embodiments, the internal power threshold model is derived from the drag attenuation benchmark function obtained above. Resistance fluctuation upper bound function and the parameters obtained from the fitting Commonly defined, this internal friction power threshold model can output the corresponding baseline resistance value and fluctuation upper limit value after inputting the cumulative shear time. All parameters obtained in the above fitting process are packaged into a complete parameter set. The parameter set is stored in the shared memory of the real-time controller of the seat testing system that combines the high and low temperature environment chamber and the robot. At the same time, the parameter freeze operation is performed. During the subsequent contact test phase, the parameter set will not be updated no matter how the robot's motion state or load changes, so as to avoid external contact force signals from contaminating the model benchmark.

[0062] In this embodiment of the invention, the viscous resistance coefficient sequence obtained through preset gravity compensation conditions and data cleaning effectively removes the influence of irrelevant factors such as gravity, inertia, and low-speed interference, truly reflecting the viscosity evolution law of grease with shear time, laying a high-quality data foundation for subsequent model construction. The internal loss power threshold model built based on this sequence, due to its deep integration with the dynamic characteristics of cumulative shear time and the constraint strategy of reusing attenuation rate parameters to ensure the robustness of the model, can match the physical laws of grease resistance attenuation and fluctuation convergence in real time, generating an internal loss benchmark that adapts to time, completely solving the problem that traditional fixed benchmarks cannot simultaneously take into account the high noise tolerance during the low-temperature start-up stage and the sensitivity of weak contact signals in the later stage. At the same time, this model does not rely on external force sensors and can achieve accurate modeling only through the operation data collected by the robot itself, providing a reliable basis for subsequent contact power extraction and seat reaction force calculation, significantly improving the force control accuracy and data reliability of seat testing in extreme low-temperature environments, and providing core technical support for the stable and efficient implementation of the entire testing method.

[0063] S203. During the robot's contact test action phase, determine the current internal power threshold based on the internal power threshold model, the current cumulative shearing duration, and the current joint rotation speed.

[0064] As one possible implementation, the current cumulative shear duration is obtained, and the internal friction power threshold model constructed in step S202 above is retrieved, with the cumulative shear duration input into the internal friction power threshold model. The internal friction power threshold model includes a resistance attenuation benchmark function based on the current cumulative shear duration to obtain a benchmark resistance value, and an upper bound function for resistance fluctuation based on the current cumulative shear duration to obtain an upper limit value for fluctuation.

[0065] Furthermore, the current joint rotation speed is obtained, and combined with the reference resistance value and the upper limit of fluctuation, the current internal power consumption threshold is obtained.

[0066] In some embodiments, the formula for determining the current internal power threshold is as follows: In the formula, Sampling time The current internal power threshold corresponding to (the current moment) Sampling time The corresponding cumulative shearing time, Based on sampling time The reference resistance value is obtained by calculating the corresponding cumulative shear time. Based on sampling time The upper limit of fluctuation is obtained by calculating the corresponding cumulative shearing time. For statistical safety, the value is a preset constant (e.g., a value of 3 corresponds to 3). (Principle) to cover random disturbances that the model does not fully represent (such as occasional fluctuations in the microstructure of grease, small noises from motor operation, etc.), and to avoid misjudgment of contact signals due to unmodeled interference. Sampling time The absolute value of the current joint rotation speed is used to convert the resistance parameter into a power parameter, eliminate the influence of the joint rotation direction on the power calculation, and focus on the power amplitude characteristics.

[0067] It should be noted that in the above formula for determining the current internal power threshold, This is an equivalent viscous drag coefficient, whose physical meaning corresponds to the equivalent torque per unit joint rotational speed under the current cumulative shear time. When this coefficient is equal to the absolute value of the current joint rotational speed (with dimensions of angular velocity)... When multiplying, the overall dimension on the right side of the equation is torque × angular velocity = power, which is consistent with the power dimension of the current internal power threshold on the left side of the equation. The current internal power threshold calculated by the above formula has significant dynamic adaptive characteristics: it increases with the current cumulative shearing time. The continuous increase in the benchmark resistance value With fluctuation upper limit Synchronous decay reduces the current internal power threshold. It exhibits a "dynamic contraction" trend. In the initial stage of the contact test, the threshold width is relatively wide, which can accommodate the high-amplitude resistance fluctuations when the grease is not completely sheared and thinned, avoiding the misjudgment of noise as a contact signal; in the later stage of the contact test, the threshold width automatically narrows, which can sensitively capture the small increment in the total drive power of the motor that exceeds the internal loss, that is, the effective power generated by the seat contact, and adapt to the time-varying law of the rheological characteristics of the grease in low-temperature environments.

[0068] Understandably, in this embodiment of the invention, the resistance attenuation benchmark function and resistance fluctuation upper bound function obtained through prior modeling ensure that the calculation basis of the internal power threshold accurately reflects the essential rheological law of the lubricating grease. Using the current cumulative shearing time as a key input allows the threshold to be adjusted in real time according to the thinning and fluctuation convergence characteristics of the lubricating grease during the shearing process, adapting to the time-varying characteristics of lubricating grease resistance in low-temperature environments. Simultaneously, incorporating the current joint rotation speed for power dimension conversion ensures a high degree of matching between the threshold and the robot's real-time motion state, avoiding threshold deviations caused by speed changes. Furthermore, the synergistic effect of the benchmark resistance value and the fluctuation upper bound ensures both the threshold's fit to the basic level of internal resistance and sufficient coverage of the influence range of random fluctuations. The current internal power threshold generated in this step possesses the core advantage of dynamic adaptation, effectively solving the problem that traditional fixed thresholds cannot simultaneously consider the anti-interference capability in the initial stage of contact testing and the sensitivity of weak signal detection in the later stage. It provides an accurate and reliable judgment benchmark for accurately separating the internal power loss component from the external contact power in the total motor drive power, significantly improving the accuracy and stability of seat contact signal detection in extreme low-temperature environments.

[0069] S204. Determine the external contact power based on the joint operation data collected during the contact test action phase and the current internal power threshold.

[0070] As one possible implementation, firstly, for each sampling moment during the contact test action phase, based on preset gravity compensation conditions, the current net output torque is determined according to the current driving current and the current joint angular acceleration.

[0071] In some embodiments, the current net output torque is obtained by combining the current drive current and the current joint angular acceleration collected at each sampling time and subtracting the inertial torque. The calculation formula is as follows: In the formula, Sampling time The current net output torque at the current moment is used to characterize the effective torque of the motor to overcome the resistance of the lubricating grease and the output contact force after deducting the effects of inertia and gravity. is the motor torque constant, an inherent electromechanical conversion parameter of the motor, used to convert drive current into electromagnetic torque; Sampling time The corresponding current drive current; The equivalent rotational inertia constant of the robot in contact posture. Since the contact test is a short-stroke indentation motion with minimal changes in joint configuration, it is still regarded as a constant and is consistent with the value used in the non-contact approach motion stage to ensure calculation consistency. Sampling time The corresponding current angular acceleration.

[0072] Furthermore, based on the current net output and the current joint speed, the total drive power output of the motor is determined, and the calculation formula is as follows: In the formula, Sampling time The total driving power at the current moment. Sampling time The corresponding current net output torque, Sampling time The corresponding current joint rotation speed, the amplitude of which reflects the speed of the pressing motion. It is the absolute value of the product of the current net output torque and the current joint speed. Taking the absolute value is to eliminate the influence of the joint movement direction (pressing or fine-tuning) on ​​the power sign and focus on the power amplitude characteristics.

[0073] Furthermore, the external contact power is determined based on the total driving power and the current internal power threshold.

[0074] In some embodiments, based on the total driving power and combined with the current internal power threshold, the internal power is stripped away through energy differential calculation to extract the external contact power generated only by seat contact. The calculation formula is as follows: In the formula, Sampling time The external contact power at the current moment is used to characterize the part of the motor output power that exceeds the internal loss threshold, that is, the effective power specifically used to drive the robot end effector to contact the seat and do work on the seat. Sampling time The corresponding total drive power; Sampling time The corresponding current internal power threshold is used to characterize the maximum power limit required for the motor to overcome the internal grease resistance when there is no external contact.

[0075] It is a non-negative truncation function used to shield spurious signals when there is no effective contact, when the total driving power Less than or equal to the current internal power threshold When the total drive power is zero, it indicates that the motor output power can only cover the internal resistance loss and no effective contact has occurred. In this case, the external contact power is forcibly set to 0. Greater than the current internal power threshold When the power exceeds the limit, the effective power for contact work is the power generated.

[0076] Understandably, in this embodiment of the invention, the purity of the net output torque and total drive power is ensured by subtracting the effects of inertia and gravity, avoiding interference from irrelevant factors in power calculation and laying a reliable foundation for subsequent power separation. Simultaneously, using the current internal power threshold as a dynamic benchmark, precise separation of internal power and external contact power is achieved through energy differential calculation. This fully adapts to the characteristics of grease resistance changing over time in low-temperature environments and effectively shields interference signals caused by internal resistance fluctuations. Furthermore, the non-negative truncation process further filters out false data when there is no effective contact, ensuring the authenticity and validity of external contact power. This step solves the problems of traditional power separation methods, such as difficulty in distinguishing between internal power loss and contact signals and weak anti-interference capabilities. It accurately extracts the effective power generated solely by seat contact, providing high-quality core input data for the accurate inverse solution of the seat reaction force. This significantly improves the accuracy and reliability of seat contact signal detection in extreme low-temperature environments, providing crucial support for the force control accuracy of the entire testing method.

[0077] S205. Determine the seat reaction force based on the external contact power, and control the robot to test the seat based on the seat reaction force.

[0078] As one possible approach, for each sampling moment during the contact test phase, the seat reaction force is obtained based on the external contact power and the linear velocity of the robot end effector along the seat pressing direction at that sampling moment.

[0079] In some embodiments, based on the principle of energy conservation, the external contact power output by the power determination unit is converted into a force signal that directly reflects the seat contact state, i.e., the seat reaction force, to ensure the accuracy and physical validity of the force signal. The formula for calculating the seat reaction force is as follows: In the formula, Sampling time The seat reaction force at the current moment is used to directly characterize the magnitude of the contact pressure exerted by the seat on the robot end effector. Sampling time Corresponding external contact power, The linear velocity of the robot's end effector along the seat pressing direction is obtained through forward kinematics calculation (based on the current joint rotation speed of the main load-bearing joint). And robot link parameters, mapping joint space motion to Cartesian space, to accurately obtain the motion rate in the end effector pressing direction. It represents the absolute value of the linear velocity, used to eliminate the influence of the end motion direction (such as fine-tuning back) on the sign of the force calculation, focusing on the magnitude characteristics of the force; It is a very small positive number, and an empirical value of 0.001 can be taken to prevent the denominator from being zero. The seat reaction force obtained by inverse solving this calculation formula can follow the changes in external contact power and robot end effector linear velocity in real time, accurately reflecting the force feedback of the seat during the pressing process.

[0080] Finally, based on the deviation between the seat reaction force and the preset target load, the position correction amount of the robot end effector is calculated through the admittance control algorithm, and motion control commands for the robot are generated based on the position correction amount.

[0081] In some embodiments, a preset target load (set according to seat testing standards, used to characterize the seat durability test, denoted as) is first obtained. The seat reaction force will be solved in real time. With preset target load Compare the two and calculate the force deviation between them. Furthermore, based on a pre-defined mass-damper-spring dynamic model, an admittance control algorithm is used to control the force deviation. Converted into position correction amount of robot end effector Among them, the admittance control algorithm achieves flexible mapping of force and position by adjusting virtual mass, damping and spring parameters, avoiding load impact caused by rigid control, and is especially suitable for the embrittlement characteristics of seat foam materials in low temperature environments, preventing seat damage.

[0082] Furthermore, based on the calculated position correction amount This generates motion control commands for the robot's main load-bearing joints. These commands include parameters such as joint speed adjustment and displacement compensation, used to drive the robot's end effector to make precise fine adjustments along the pressing direction. When the seat reaction force... Below the preset target load When the allowable error range is met, the robot end effector increases the indentation depth to enhance the contact force; when the seat reaction force... Higher than the preset target load When the allowable error range is within the acceptable range, the robot end effector should be controlled to retract appropriately to reduce the contact force; when Stabilize at the preset target load When the allowable error range is within the acceptable range, maintain the current indentation depth to ensure a constant load.

[0083] In some embodiments, the seat testing system, which combines a high- and low-temperature environmental chamber and a robot, continuously executes the above-described "force inverse kinematics-admittance control-command generation" steps in each control cycle to dynamically maintain a stable load on the seat. This control cycle will continue until any of the following preset test termination conditions are met.

[0084] Termination condition 1: Seat reaction force determined at multiple consecutive moments. All are under the preset target load Within the allowable error range.

[0085] Termination condition two: The robot end effector reaches the preset travel limit (safe travel limit) when it presses into the seat.

[0086] When any termination condition is met, the current test action is determined to be completed, and the robot is then controlled to smoothly retreat along the preset trajectory, ending the current test cycle.

[0087] Understandably, in the seat testing method combining a high-low temperature environment chamber and a robot provided in this embodiment of the invention, there is no need to rely on external force sensors that are prone to failure in low-temperature environments. Accurate detection and control of seat contact force can be achieved solely through joint operation data collected by the robot itself, significantly reducing testing costs and maintenance difficulty. By constructing an internal power threshold model that dynamically changes with the cumulative shearing time through data analysis of the non-contact approach phase, it adapts to the rheological characteristics of joint grease resistance attenuation and fluctuation convergence in low-temperature environments. This completely solves the problem that traditional fixed threshold methods cannot simultaneously address both anti-interference capabilities in the initial testing phase and sensitivity in detecting weak contact signals in the later stages. The system addresses the challenges of temperature control; simultaneously, from the timing synchronization of data acquisition and the purification of viscous drag coefficient, to the precise separation of external contact power and the real-time inverse solution of seat reaction force, and then to the adjustment of robot motion based on admittance control, the entire process is progressive and logically closed-loop, effectively eliminating interference from irrelevant factors such as gravity, inertia, and speed changes, ensuring the purity of contact force detection and the smoothness of control. This not only avoids damage to the seat's brittle materials due to rigid control at low temperatures, but also significantly improves the force control accuracy, data reliability, and test stability of seat durability testing under extreme temperature conditions, fully meeting the industry's stringent requirements for seat performance testing under extreme climatic conditions.

[0088] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0089] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for testing seats combining a high and low temperature environment chamber and a robot, characterized in that, The method includes: The robot is controlled to sequentially perform non-contact approach and contact test actions, and the joint operation data of the robot is continuously collected. The joint operation data includes drive current, joint rotation speed and joint angular acceleration. Based on the joint running data collected during the non-contact approach phase, a viscous resistance coefficient sequence reflecting the rheological properties of the grease within the joint is determined. Based on the viscous resistance coefficient sequence, an internal power threshold model that varies with the cumulative shear duration is constructed, whereby the cumulative shear duration is used to characterize the total duration of shear action on the grease. During the stage when the robot performs the contact test action, the current internal power threshold is determined based on the internal power threshold model, the current cumulative shearing time, and the current joint rotation speed. The external contact power is determined based on the joint operation data collected during the contact test phase and the current internal power threshold. The seat reaction force is determined based on the external contact power, and the robot is controlled to test the seat based on the seat reaction force.

2. The seat testing method combining a high and low temperature environment chamber and a robot according to claim 1, characterized in that, The robot is controlled to sequentially execute non-contact approach actions and contact test actions, and the joint operation data of the robot is continuously collected, including: The robot is controlled to first perform the non-contact approach action and simultaneously start timing to obtain the cumulative shearing time; After the robot's end effector moves to a preset position above the seat, the robot is controlled to perform the contact test action; During the process of the robot performing the non-contact approach action and the contact test action, the joint operation data of the robot's main load-bearing joint is collected synchronously at a fixed control cycle. The main load-bearing joint is the joint that undertakes the main driving task in the seat indentation test and whose movement contributes the most to the displacement of the robot's end effector in the direction of gravity.

3. The seat testing method combining a high and low temperature environment chamber and a robot according to claim 1, characterized in that, Based on the joint movement data collected during the non-contact approach phase, a sequence of viscous drag coefficients reflecting the rheological properties of the intra-articular grease is determined, including: For each sampling moment in the non-contact approach phase, based on the preset gravity compensation conditions, the net grease resistance torque corresponding to the sampling moment is determined according to the driving current and the joint angular acceleration collected at the sampling moment. The net grease resistance torque is the net resistance generated by the lubricating grease. Based on the joint rotation speed at the sampling time and the grease resistance torque, the viscous resistance coefficient corresponding to the sampling time is determined. The viscous resistance coefficient is used to reflect the viscosity characteristics of the grease. The viscous drag coefficient sequence is obtained by removing viscous drag coefficients whose absolute values ​​of joint rotation speed are lower than a preset rotation speed threshold at multiple sampling times.

4. The seat testing method combining a high and low temperature environment chamber and a robot according to claim 1, characterized in that, Based on the viscous drag coefficient sequence, a power dissipation threshold model varying with cumulative shear time is constructed, including: The viscous resistance coefficient sequence is fitted with a function to obtain a resistance attenuation benchmark function, which is used to reflect the attenuation law of the macroscopic resistance of the grease with shear time. Determine the residual of each data point in the viscous drag coefficient sequence relative to the drag attenuation reference function; Using the attenuation rate parameter included in the resistance attenuation benchmark function as a constraint, the residual is fitted with an upper envelope to obtain the resistance fluctuation upper bound function, which is used to define the maximum statistical fluctuation range of resistance. The internal power threshold model is constructed based on the resistance attenuation benchmark function and the resistance fluctuation upper bound function.

5. The seat testing method combining a high and low temperature environment chamber and a robot according to claim 4, characterized in that, By performing function fitting on the viscous drag coefficient sequence, a drag attenuation benchmark function is obtained, including: An exponential decay function model is constructed, which includes a first parameter for characterizing steady-state impedance, a second parameter for characterizing the magnitude of change, and a third parameter for characterizing viscosity decay rate. The initial value of the first parameter is determined based on the statistical characteristics of the data located at the end of the viscous drag coefficient sequence and accounting for a first preset proportion. The initial value of the second parameter is determined based on the statistical characteristics of the data located at the beginning of the viscous drag coefficient sequence and accounting for a second preset proportion, and the initial value of the first parameter. Set an initial value for the third parameter; Using the initial values ​​of the first, second, and third parameters as the starting point for iteration, the exponential decay function model is fitted using a nonlinear optimization algorithm to determine the drag decay benchmark function.

6. The seat testing method combining a high and low temperature environment chamber and a robot according to claim 4, characterized in that, Based on the internal power threshold model, the current cumulative shearing duration, and the current joint rotation speed, the current internal power threshold is determined, including: The current cumulative shear duration is input into the internal friction power threshold model. The internal friction power threshold model includes a resistance attenuation benchmark function that, based on the current cumulative shear duration, obtains a benchmark resistance value. The internal friction power threshold model also includes a resistance fluctuation upper bound function that, based on the current cumulative shear duration, obtains a fluctuation upper limit value. The current internal power consumption threshold is obtained based on the reference resistance value, the upper limit of fluctuation, and the current joint speed.

7. The seat testing method combining a high and low temperature environment chamber and a robot according to claim 1, characterized in that, Based on the joint operation data collected during the contact test phase and the current internal power threshold, the external contact power is determined, including: Based on preset gravity compensation conditions, the current net output torque is determined according to the current drive current and the current joint angular acceleration. The total drive power currently output by the motor is determined based on the current net output torque and the current joint speed. The external contact power is determined based on the total driving power and the current internal power threshold.

8. The seat testing method combining a high and low temperature environment chamber and a robot according to claim 1, characterized in that, The system determines the seat reaction force based on the external contact power and controls the robot to test the seat based on the seat reaction force, including: The reaction force of the seat is obtained based on the external contact power and the linear velocity of the robot end effector along the seat pressing direction. Based on the deviation between the seat reaction force and the preset target load, the position correction amount of the robot end effector is calculated by the admittance control algorithm, and motion control commands for the robot are generated based on the position correction amount.

9. The seat testing method combining a high and low temperature environment chamber and a robot according to claim 1, characterized in that, The method further includes: If the reaction force of the seat is determined to be within the allowable error range of the preset target load at multiple consecutive moments, or if the indentation depth of the robot end relative to the seat reaches the preset travel limit, the robot is controlled to exit the test.

10. A seat testing system combining a high and low temperature environment chamber and a robot, characterized in that, include: The data acquisition unit is used to control the robot to sequentially perform non-contact approach actions and contact test actions, and to continuously collect the joint operation data of the robot, including drive current, joint rotation speed and joint angular acceleration. The model building unit is used to determine the viscous resistance coefficient sequence reflecting the rheological properties of the grease in the joint based on the joint running data collected during the non-contact approach phase, and to build an internal power threshold model that varies with the cumulative shear time based on the viscous resistance coefficient sequence. The internal friction threshold determination unit is used to determine the current internal friction power threshold based on the internal friction power threshold model, the current cumulative shearing time, and the current joint rotation speed during the stage when the robot performs the contact test action. A power determination unit is used to determine the external contact power based on the joint operation data collected during the contact test action phase and the current internal power threshold. The control unit is used to determine the seat reaction force based on the external contact power, and control the robot to test the seat based on the seat reaction force.

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