Dynamic matching method, device, system and medium of electric drive system based on load spectrum driving, and product

Abstract

This invention relates to the field of electric drive technology, and particularly to a dynamic matching method, device, system, medium, and product for electric drive systems based on load spectrum driving. The method includes: acquiring load spectrum data based on the operating conditions of the electric drive system and the fatigue work cycle table of engineering machinery; classifying the load spectrum data, judging the motor's overload suitability, and compiling a cyclic load spectrum; obtaining the motor's theoretical temperature rise result and the motor's thermal simulation temperature result; dynamically adjusting the motor's thermal capacitance coefficient and thermal resistance coefficient based on the obtained motor theoretical temperature rise result and motor thermal simulation temperature result; and outputting the final motor thermal capacitance coefficient and motor thermal resistance coefficient. For redundancy optimization in motor overload matching, a closed-loop process of drive system load spectrum acquisition – load spectrum analysis – overload temperature rise theoretical calculation – motor thermal simulation verification is used to solve the problems of excessive redundancy, insufficient dynamic adaptability, and poor economy in traditional motor selection.

Description

Technical Field

[0001] This invention relates to the field of electric drive technology, and in particular to a dynamic matching method, device, system, medium, and product for an electric drive system based on load spectrum driving. Background Technology

[0002] The transmission system of traditional engineering machinery mainly consists of a torque converter, a gearbox, a drive shaft, and a drive axle. The drive shaft, as the input shaft of the drive axle, inputs torque and speed to the drive axle to achieve movement.

[0003] Existing matching technologies for electric drive systems generally use static operating condition calculations as design inputs. The rated performance of the matched motor meets the theoretical peak performance calculated by the load unit (e.g., torque is usually reserved with a 30%-50% margin) to achieve a safe and redundant design for the system. While this method can ensure the load safety of the equipment under extreme conditions (such as heavy-load start-stop, instantaneous material accumulation), it has the following significant drawbacks: ① Excessive redundancy design: Using a constant safety factor to cover dynamic load scenarios leads to motor specifications that far exceed actual needs. For example, the measured peak torque of a certain type of electric product's transmission system is 1800 N / m, while the rated torque of the matching motor is as high as 2400 N / m (redundancy factor of 1.33), directly causing a 15%-20% increase in motor cost and size, reducing the system's economy; ② Imbalance between cost and energy efficiency: Since the actual dynamic load is mostly far below the rated performance of the motor, the motor will operate in the low load range for a long time (usually 30%-50% of the rated torque). Its efficiency curve deviates from the high efficiency range, resulting in a decrease in overall energy efficiency and indirectly increasing the power consumption cost of the equipment's life cycle by about 20%. ③ Dynamic operating condition mismatch: The static calculation selection method does not consider the dynamic fluctuation characteristics of the load (such as the difference between short-term impact load and continuous overload), and still relies on general design standards, sacrificing the power density and dynamic characteristics of the electric drive system. ④ Insufficient data-driven approach: The lack of existing engineering machinery testing technology leads to limitations in the acquisition of transmission system load spectrum data and the collection of operating conditions. This results in the inability to provide accurate transmission system load spectrum data, causing current electric drive transmission designs to rely on theoretical steady-state operating condition calculations. It is difficult to accurately quantify the source of design input data, thus making it impossible to achieve efficient and accurate motor matching applications.

[0004] Therefore, it is necessary to provide a new dynamic matching method for electric drive systems to solve the above-mentioned technical problems. Summary of the Invention

[0005] The main objective of this invention is to provide a dynamic matching method for electric drive systems based on load spectrum, which optimizes redundancy for motor overload matching. Through a closed-loop process—load spectrum acquisition, load spectrum analysis (including load spectrum classification, motor overload suitability assessment, and cyclic load spectrum compilation), and overload temperature rise simulation application verification (obtaining theoretical motor temperature rise results and motor thermal simulation temperature results, and dynamically adjusting the motor's thermal capacity coefficient and thermal resistance coefficient to achieve accurate motor temperature rise calculation)—this invention provides a preliminary verification method for the economical design of motors based on actual load spectrum requirements. It addresses the problems of excessive redundancy, insufficient dynamic adaptability, and poor economy in traditional motor selection. The specific technical solution is as follows: A dynamic matching method for an electric drive system based on load spectrum drive includes the following steps: Step S1: Load spectrum acquisition of the transmission system, specifically: obtain load spectrum data based on the operating conditions of the electric drive system and the fatigue working cycle table of the engineering machinery; Step S2, load spectrum analysis, specifically: based on the load spectrum data obtained in step S1, perform load spectrum classification, motor overload applicability judgment and cyclic load spectrum compilation, and output the cyclic load spectrum of the motor throughout its entire life cycle and the cyclic loading table of the motor throughout its entire life cycle. Step S3: Obtain the theoretical temperature rise result of the motor. Specifically, based on the motor thermal balance equation, establish a dynamic model of heat generation and heat dissipation power under load conditions; input parameters include the motor's thermal capacity coefficient, the motor's thermal resistance coefficient, and the ambient temperature; map the operating points of the motor's full life cycle cyclic loading table obtained in step S2 to the motor MAP to find the power loss at the corresponding points; solve for the theoretical temperature rise result of the motor at the operating points of the cyclic loading table. To obtain the motor thermal simulation temperature results, specifically: construct a motor thermal simulation model; input the full life cycle loading table obtained in step S2 into the motor thermal simulation model, drive the motor to run, and output the motor thermal simulation temperature results; Step S4: Based on the theoretical temperature rise result of the motor obtained in step S3 and the temperature result of the motor thermal simulation, dynamically adjust the thermal capacity coefficient and thermal resistance coefficient of the motor; output the final thermal capacity coefficient and thermal resistance coefficient of the motor.

[0006] Preferably, in step S1: the operating conditions of the electric drive system include road type, terrain, traffic conditions, driving style, load weight, and equipment usage type; the fatigue work cycle table of the construction machinery is obtained based on the operating conditions of the electric drive system and the equipment operation work cycle; the load spectrum data includes the torque and speed of the drive shaft.

[0007] Preferably, a strain gauge mounted on the drive shaft is used to perform torsional strain testing, and the measured torsional strain is calibrated to obtain the torque of the drive shaft; a photoelectric speed sensor is used to test the speed of the drive shaft to obtain the speed of the drive shaft.

[0008] Preferably, the load spectrum classification in step S2 specifically involves extracting dynamic characteristic parameters of the torque load spectrum. These dynamic characteristic parameters include: time-domain indicators, such as peak torque, mean torque, volatility, and duration; and frequency-domain indicators, such as energy concentration frequency band and impact response frequency.

[0009] Preferably, the load spectrum categories include steady torque spectrum, short-term overload torque spectrum, periodic fluctuation torque spectrum, stable fluctuation torque spectrum, and continuous fluctuation load spectrum.

[0010] Preferably, the motor overload applicability judgment in step S2 is as follows: the motor overload rate refers to the percentage by which the actual operating load of the motor exceeds its rated load, that is, the motor overload rate = peak torque required by the load spectrum / rated torque of the motor configuration; When the peak torque required by the load spectrum is less than or equal to the rated torque of the motor, the motor overload rate is 1, and there is no overload. When the peak torque required by the load spectrum is greater than the rated torque of the motor, the motor overload rate is greater than 1, indicating overload.

[0011] Preferably, the cyclic load spectrum compilation is specifically as follows: based on the rainflow counting method and extreme value statistics theory, the load frequency and amplitude are synchronously extrapolated and the overload multiple is adjusted; according to the time-frequency characteristics of the load spectrum, the overload period is inserted into the full life cycle standard cyclic spectrum to form the set overload test verification spectrum, and the output includes the full life cycle cyclic load spectrum of the motor and the full life cycle cyclic loading table of the motor.

[0012] Preferably, in step S3, the operating points of the motor's full life cycle cyclic loading table obtained in step S2 are mapped to the power loss at the corresponding points in the motor MAP. The standard solution is as follows: ; in: for The temperature rise of the motor relative to the ambient temperature at any given time; The ambient temperature; The thermal capacity coefficient of the motor; The thermal resistance coefficient of the motor; This represents the power loss value of the motor. , This refers to the input electrical power of the motor. The output mechanical power of the motor. The efficiency at the motor's operating point; For time.

[0013] Preferably, the dynamic adjustment of the motor's thermal capacity coefficient and thermal resistance coefficient based on the motor's theoretical temperature rise result and motor thermal simulation temperature result obtained in step S3 in step S4 specifically means: making the deviation rate between the motor's theoretical temperature rise result and motor thermal simulation temperature result <3%.

[0014] The effect of applying the technical solution of this invention is: 1. The dynamic matching method for electric drive transmission systems based on load spectrum driving disclosed in this invention includes: load spectrum acquisition of the transmission system, specifically: acquiring load spectrum data based on the operating conditions of the electric drive system and the fatigue working cycle table of engineering machinery; load spectrum analysis, specifically: classifying the load spectrum data, judging the overload applicability of the motor, and compiling the cyclic load spectrum, outputting a cyclic load spectrum including the full life cycle of the motor and a cyclic loading table of the full life cycle of the motor; obtaining the theoretical temperature rise result of the motor, specifically: establishing a dynamic model of heat generation and heat dissipation power under load conditions based on the motor thermal balance equation; input parameters include the thermal capacity coefficient of the motor. The process involves: determining the motor's thermal resistance coefficient and ambient temperature; mapping the operating points of the obtained full-lifecycle cyclic loading table to the corresponding points in the motor MAP to find the power loss; calculating the theoretical temperature rise of the motor at the operating points in the cyclic loading table; obtaining the motor thermal simulation temperature results, specifically: constructing a motor thermal simulation model; inputting the obtained full-lifecycle cyclic loading table into the motor thermal simulation model, driving the motor to run, and outputting the motor thermal simulation temperature results; dynamically adjusting the motor's thermal capacity coefficient and thermal resistance coefficient based on the obtained theoretical temperature rise and motor thermal simulation temperature results; and finally outputting the motor's thermal capacity coefficient and thermal resistance coefficient. For motor overload matching to achieve redundancy optimization, a closed-loop process of transmission system load spectrum acquisition - load spectrum analysis - overload temperature rise theoretical calculation - motor thermal simulation verification is used to solve the problems of excessive redundancy, insufficient dynamic adaptability, and poor economy in traditional motor selection. This achieves a precise and economical matching method by matching motor performance to actual load requirements.

[0015] 2. In this invention, load spectrum data is obtained based on the operating conditions of the electric drive system and the fatigue working cycle table of engineering machinery, and a multi-dimensional load acquisition and operating condition evaluation system is established to obtain an accurate and comprehensive equipment operating condition load database.

[0016] 3. This invention classifies load spectra, determines the applicability of motor overload, and compiles cyclic load spectra based on the obtained load spectrum data. The output includes a cyclic load spectrum and a cyclic loading table covering the entire lifecycle of the motor. It comprehensively considers the characteristics of the equipment's load conditions, identifying the duration, frequency, and time interval of continuous and peak operating conditions. The load spectrum types are then categorized, and a graded assessment of the feasibility of overload utilization is implemented. Load spectrum reconstruction technology is used to perform time-frequency domain feature analysis and dynamic adjustment on the selected load units, generating a load spectrum representing all operating conditions and limit values ​​throughout the equipment's entire lifecycle.

[0017] 4. This invention establishes a calculation and verification system for motor overload temperature rise. Based on the motor thermal balance equation, a dynamic model of heat generation and heat dissipation power under load conditions is established. A theoretical calculation method for motor temperature rise is developed, enabling rapid thermal assessment of motor overload matching. Combined with subsequent motor thermal simulation analysis, a closed-loop analysis and verification method for motor overload temperature rise is realized. This method breaks through the static threshold limitation of traditional overload matching. Under the premise of ensuring safe operation of equipment, it significantly improves the efficiency and adaptability of motor system, effectively reduces motor configuration costs, and improves the overall energy consumption economy.

[0018] The present invention also provides a dynamic matching device for an electric drive transmission system based on load spectrum driving, comprising: The data acquisition module is used to obtain load spectrum data based on the operating conditions of the electric drive system and the fatigue work cycle table of the construction machinery. The load spectrum analysis module is used to analyze load spectrum data and outputs a cyclic load spectrum of the motor throughout its entire life cycle and a cyclic loading table of the motor throughout its entire life cycle. The motor temperature rise theory processing module is used to establish a dynamic model of heat generation and heat dissipation power under load conditions based on the motor thermal balance equation, and to solve the theoretical temperature rise results of the motor at the working point of the cyclic loading table by combining the motor full life cycle cyclic loading table. The motor thermal simulation processing module is used to build a motor thermal simulation model, input the full life cycle loading table into the motor thermal simulation model to drive the motor to run, and output the motor thermal simulation temperature results. The electric drive system matching module combines the theoretical temperature rise results of the motor with the thermal simulation temperature results of the motor to dynamically adjust the thermal capacity coefficient and thermal resistance coefficient of the motor.

[0019] Preferably, the load spectrum analysis module includes: a load spectrum classification submodule, used to classify the load spectrum data and output the dynamic characteristic parameters of the torque load spectrum; a motor overload judgment submodule, used to screen and judge whether the motor is overloaded based on the motor overload rate and output the motor overload result; and a cyclic load spectrum compilation submodule, used to extrapolate the extreme values ​​of the load spectrum and arrange the time sequence, and output a cyclic load spectrum containing the motor's entire life cycle and a cyclic loading table containing the motor's entire life cycle.

[0020] The present invention also provides a dynamic matching system for an electric drive system, the dynamic matching system for an electric drive system comprising: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the load spectrum-driven dynamic matching method for an electric drive system as described above.

[0021] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described dynamic matching method for an electric drive system based on load spectrum driving.

[0022] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described dynamic matching method for an electric drive transmission system based on load spectrum driving. Attached Figure Description

[0023] To more clearly illustrate the technical solutions 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 the structures shown in these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the dynamic matching method for an electric drive transmission system based on load spectrum driving in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the data acquisition scheme in Embodiment 1 of the present invention; Figure 3(a) is a schematic diagram of the steady torque spectrum in Embodiment 1 of the present invention; Figure 3(b) is a schematic diagram of the short-time overload torque spectrum in Embodiment 1 of the present invention; Figure 3(c) is a schematic diagram of the periodic fluctuation type torque spectrum in Embodiment 1 of the present invention; Figure 3(d) is a schematic diagram of the stable fluctuation type torque spectrum in Embodiment 1 of the present invention; Figure 3(e) is a schematic diagram of the continuous fluctuation type load spectrum in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the torque-time history in Embodiment 1 of the present invention; Figure 5 This is a schematic diagram of the segmented equivalent torque in Embodiment 1 of the present invention; Figure 6 This is a MAP diagram of the motor in Embodiment 1 of the present invention.

[0025] Explanation of reference numerals in the attached figures: A - Drive motor, B - Reduction gearbox, C - Front drive shaft, D - Rear drive shaft, E - Front drive axle, F - Rear drive axle, G - Photoelectric speed sensor.

[0026] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0028] Example 1: A dynamic matching method for electric drive systems based on load spectrum drive is presented. Specifically, it is a matching method for electric drive systems based on load spectrum analysis input of traditional systems. It focuses on optimizing redundancy through motor overload matching. Through a closed-loop process of load spectrum acquisition, load characteristic analysis, overload necessity decision-making, overload spectrum compilation, overload temperature rise verification, and application verification, it solves the problems of excessive redundancy, insufficient dynamic adaptability, and poor economy in traditional motor selection. Figure 1 As shown, it includes: transmission system load spectrum acquisition, load spectrum classification, motor overload suitability determination, cyclic load spectrum compilation, motor performance parameter input, motor theoretical temperature calculation and motor thermal simulation analysis calculation, and motor thermal parameter correction. In addition, it may also include theoretical verification of overload conditions and motor overload test verification.

[0029] The dynamic matching method for electric drive systems based on load spectrum driving in this embodiment specifically includes the following steps: Step S1: Load spectrum acquisition of the transmission system, specifically: obtain load spectrum data based on the operating conditions of the electric drive system and the fatigue working cycle table of the engineering machinery.

[0030] In this embodiment, the specific test conditions are as follows: A survey of the product's transmission system operating conditions is conducted based on the product's main sales regions. The survey sample should cover typical user types, forming user operating conditions, including but not limited to road type, terrain, traffic conditions, driving style, load weight, and equipment usage type, as shown in Table 1. Table 1 User Usage Status Table

[0031] In this embodiment, the test cycle is specifically as follows: Based on the comprehensive on-site survey and definition of operating conditions, and the equipment's working cycle, a statistical table of fatigue working cycles during equipment use is provided. The fatigue working cycle should be the working cycle under typical operating conditions of the equipment. Typical fatigue working cycles of engineering machinery are shown in Table 2. Table 2. Statistical Table of Typical Fatigue Working Cycles for Engineering Machinery

[0032] The data acquisition scheme in this embodiment is as follows: The main data acquisition units are the torque and speed signals of the front and rear drive shafts. The designed acquisition scheme is as follows: Figure 2 As shown, torsional strain testing of the drive shaft was performed using strain testing technology. The strain gauges were attached to the C and D drive shafts. Two sets of shear gauges were used, which were attached to the upper and lower surfaces of the shafts respectively to form a Wheatstone full bridge.

[0033] The measured torsional strain was calibrated using a strain-torque method. The calibration bench and method for the drive shaft torque sensor are as follows: a) Calibration was performed using the lever arm method, with a lever arm length of 1m; b) Weights were loaded to the full range, and the weight of the weights was transferred to the drive shaft to achieve torque loading; c) The loading was repeated 5 times; d) The drive shaft torque was calibrated by establishing the relationship between torque and the output strain of the measurement circuit to obtain an accurate torque load spectrum (repeatability deviation <3%). This was achieved by installing a high-frequency torque sensor (sampling rate ≥1kHz) on the drive shaft.

[0034] A photoelectric speed sensor is used to test the rotational speed of the drive shaft. A reflective label is attached to the drive shaft, and the photoelectric speed sensor identifies and records the number of rotations of the drive shaft. In other words, a Hall effect speed sensor is installed on the drive shaft.

[0035] Step S2, Load Spectrum Analysis, specifically involves: classifying the load spectrum based on the load spectrum data obtained in Step S1, determining the motor's overload suitability, and compiling the cyclic load spectrum. The output includes the cyclic load spectrum of the motor's entire lifecycle and a cyclic loading table of the motor's entire lifecycle. Details are as follows: In this embodiment, the basis for classifying the load spectrum is to extract the dynamic characteristic parameters of the torque load spectrum. The dynamic characteristic parameters of the torque load spectrum include: time-domain indicators, including peak torque, mean torque, volatility, and duration; and frequency-domain indicators, including energy concentration frequency band and impact response frequency.

[0036] In this embodiment, the load spectrum categories include steady-state torque spectrum, short-term overload torque spectrum, periodic fluctuation torque spectrum, stable fluctuation torque spectrum, and continuous fluctuation load spectrum, as detailed below: ① Stable torque spectrum: The load operates basically stably (torque change rate <10%), and no overload events occur, as shown in Figure 3(a).

[0037] ② Short-term overload torque spectrum: The duration of a single overload is ≤30s (the minimum time for peak torque to be sustained as defined by the national standard for motors), and the peak torque is 1.1-2.5 times the rated value, as shown in Figure 3(b).

[0038] ③ Periodic fluctuation type torque spectrum: Overload events repeat periodically, with an interval time ≥ 2 times the duration of a single overload, as shown in Figure 3(c).

[0039] ④ Stable fluctuation type torque spectrum: The load changes in a step-like manner, and the torque fluctuation in each gradient segment is small (torque change rate <10%), as shown in Figure 3(d).

[0040] ⑤ Continuous fluctuation type load spectrum: The load fluctuation has no obvious regularity, the fluctuation rate and fluctuation interval change randomly, and the load unit has strong dynamics, as shown in Figure 3(e).

[0041] In this embodiment, the determination of motor overload suitability is specifically as follows: Motor overload rate refers to the percentage by which the actual operating load of a motor exceeds its rated load, i.e., motor overload rate = peak torque required by the load spectrum / rated torque of the motor configuration; When the peak torque required by the load spectrum is less than or equal to the rated torque of the motor, the motor overload rate is 1, and there is no overload. When the peak torque required by the load spectrum is greater than the rated torque of the motor, the motor overload rate is greater than 1, indicating overload.

[0042] Based on the operating characteristics of motors in the construction machinery industry, the overload rate range of motors is generally [1, 3].

[0043] In this embodiment, the determination of the applicability of motor overload is as follows: ① Load differentiation: Overload strategy is given priority for short-term overload torque spectrum loads, while overload utilization is not considered for stable fluctuation torque spectrum and steady fluctuation torque spectrum; ② Economic benefit assessment: If overload can reduce the rated torque of the motor by ≥20%, it is determined that overload application design is feasible; ③ Motor temperature rise assessment: For motors with progressive overload, temperature rise calculation based on load spectrum is performed. The feasibility of motor overload is verified by temperature rise (maximum overload temperature < motor insulation temperature), and it is determined that overload application design is feasible.

[0044] In this embodiment, the cyclic loading spectrum is specifically compiled as follows: The compilation method specifically includes amplitude optimization and timing arrangement, among which: Amplitude optimization: Rainflow counting and amplitude extrapolation are performed on the load spectrum data for each operating condition type (steady-state, impact, periodic). Combined with the maximum output characteristics of the design power source (such as the engine of the prototype diesel equipment) and the maximum adhesion torque of the vehicle, the limiting torque for each operating condition is corrected. ,Right now: ; in: Extrapolation of the torque load spectrum ; This is the maximum input torque of the power source. , This is the maximum pitch coefficient of the torque converter. For the gearbox speed ratio, (Transmission efficiency of the power source). This is the maximum adhesion torque of the entire vehicle. , The ground adhesion coefficient, For vehicle weight load, The radius of the wheel's rolling motion. For the axle speed ratio, This refers to the overall transmission efficiency of the vehicle.

[0045] Timing arrangement: Based on the time-frequency characteristics of the load spectrum, the overload period is inserted into the full life cycle standard cyclic spectrum to form the set overload test verification spectrum.

[0046] Output format: Generates an executable control instruction set containing a full lifecycle cyclic load spectrum and a full lifecycle cyclic loading table. Since the full lifecycle cyclic load spectrum is a load-time history, such as... Figure 4 As shown, performing load temperature rise calculations or simulations at all time points would significantly increase the computational requirements and workload. Therefore, it is necessary to convert the cyclic load-time history into a single loading table for each operating point. Based on the torque change rate dT / dt, the continuous load spectrum is divided into N approximately stable intervals. The equivalent values ​​of torque and speed for each segment are calculated. This satisfies the loading effect of each rate of change throughout the entire life cycle while reducing the computational workload. This transforms the load-time history of a certain operating condition into a single load and time loading point. Based on the motor operating temperature rise calculation formula described later, the temperature deviation value of each division step is calculated. A rationality judgment is made in the early stage of scheme design: ① If the load change rate ΔT% ≤ 3%, pre-segmentation is performed to generate a multi-point loading spectrum; ② If the step temperature deviation is Δt% ≤ 5%, the segmentation results are checked. If it exceeds 5%, the segmentation is further refined; ③ The calculation method for the equivalent torque value of each segment is as follows: ; in: For the first Segmented equivalent torque; for The torque value at any given moment; The duration of the segmented torque.

[0047] The equivalent speed of each segment is calculated and matched to the design speed under operating conditions: ; in: For the first Segmented equivalent speed; Design speed.

[0048] Based on the above calculation method, a piecewise equivalent torque is designed as follows: Figure 5 The calculated cyclic loading table for the entire life cycle of the driving motor of a certain product is shown in Table 3: Table 3. Cyclic Loading Table of the Travel Motor of a Certain Product Throughout its Life Cycle

[0049] Step S3: Obtain the theoretical temperature rise result of the motor. Specifically, based on the motor thermal balance equation, establish a dynamic model of heat generation and heat dissipation power under load conditions; input parameters include the motor's thermal capacity coefficient, the motor's thermal resistance coefficient, and the ambient temperature; map the operating points of the motor's full life cycle cyclic loading table obtained in step S2 to the motor MAP to find the power loss at the corresponding points; solve for the theoretical temperature rise result of the motor at the operating points of the cyclic loading table. To obtain the motor thermal simulation temperature results, specifically: construct a motor thermal simulation model; input the full life cycle loading table obtained in step S2 into the motor thermal simulation model, drive the motor to run, and output the motor thermal simulation temperature results.

[0050] The preferred theoretical model for motor temperature rise in this embodiment is constructed as follows: Based on the motor thermal balance equation, a dynamic model of heat generation and heat dissipation under load conditions is established, and a theoretical calculation method for motor temperature rise ΔT is developed. Input parameters include motor performance parameters (provided by the motor manufacturer) and heat capacity coefficient. Thermal resistance coefficient Ambient temperature .

[0051] The mathematical expression of the differential equation (energy conservation) for the thermal balance of a motor is as follows, which describes the dynamic process of the motor temperature changing over time: ; in: for The temperature rise of the motor relative to the ambient temperature at any given time, expressed in °C or K. The thermal capacity coefficient of an electric motor is the ability of the motor windings and core to store heat, expressed in J / ℃ or J / K. It is the thermal resistance coefficient of the motor, which is the resistance to heat dissipation from the windings to the environment, and is expressed in °C / W or K / W. This is the power loss value of the motor, which is the total loss generated inside the motor (copper loss + iron loss + mechanical loss), and the unit is kW; The time unit is seconds (s).

[0052] Therefore, we can conclude that: ; That is, the heat stored by temperature changes + the heat lost through thermal resistance = the heat generated by internal losses.

[0053] Solving the above heat balance equation and mapping the operating points of the motor's full life cycle cyclic loading table to the motor MAP to find the power loss at the corresponding points, the standard solution form is as follows: ; The formula for calculating the power loss at the motor's MAP operating point is as follows: ; in: This refers to the input electrical power of the motor. The output mechanical power of the motor. This refers to the motor's operating efficiency, which is a built-in attribute table of the motor: torque-speed-efficiency. For a moment.

[0054] The motor MAP diagram in this embodiment is as follows: Figure 6 As shown.

[0055] The temperature rise calculation results for the cyclic loading table operating points are shown in Table 4. Table 4 Temperature rise calculation results at the operating point of the cyclic loading table

[0056] In this embodiment, the designed full life cycle cyclic loading table is input into the motor thermal simulation model to drive the motor. The output thermal discharge temperature is shown in Table 5. Table 5 Simulation data of motor thermal temperature rise at operating point

[0057] Step S4: Based on the theoretical temperature rise result of the motor obtained in step S3 and the temperature result of the motor thermal simulation, dynamically adjust the thermal capacity coefficient and thermal resistance coefficient of the motor; output the final thermal capacity coefficient and thermal resistance coefficient of the motor.

[0058] In this embodiment, the dynamic adjustment of the motor's thermal capacity coefficient and thermal resistance coefficient based on the theoretical temperature rise result and the motor thermal simulation temperature result obtained in step S3 is specifically: to ensure that the deviation rate between the theoretical temperature rise result and the motor thermal simulation temperature result is <5%. This calibrates the deviation of the motor thermal balance temperature calculation formula, enabling rapid preliminary verification of the cyclic load spectrum of the motor under various operating conditions. See Table 6 for details. Table 6. Preliminary Calculation Results of Cyclic Load Spectrum for Motors under Various Operating Conditions

[0059] The technical solution applied in this embodiment also includes the following: I. Overload reliability requirements for motors: Motor circulating temperature rise < motor allowable temperature rise (determined by motor type and model); The maximum temperature under continuous overload of the motor is less than the motor insulation temperature (determined by the motor type and model). The time it takes for a motor to withstand continuous overload to reach its insulation temperature is greater than the longest required time for continuous overload under operating conditions (determined by the equipment's operating conditions).

[0060] II. Implementation of Control Strategy: If the load exceeds the rated value and the duration is less than or equal to the model's allowable value (e.g., 30 seconds), then maintain overload operation; if the overload time is close to the threshold, then activate auxiliary cooling and reduce the subsequent load rate (e.g., force the system to run at 80% rated load for 5 minutes).

[0061] III. Protection Mechanism: When the winding temperature is greater than or equal to the insulation class limit (e.g., 155℃ for Class H), immediately reduce the load to the rated load (the specific reduction range is determined by the motor overload verification data).

[0062] By applying the technical solution of this embodiment, the present invention significantly reduces redundant design costs and improves system energy efficiency and operating condition adaptability by coupling load spectrum characteristic analysis with the dynamic overload performance of the motor, while ensuring motor safety. Details are as follows: (1) Accurately match load requirements and reduce equipment configuration costs. Specifically: ① Redundancy optimization: By screening out unnecessary redundant scenarios (such as short-term impact loads) through overload necessity screening, the rated torque of the motor can be reduced by 10%-20%; ② Volume and weight reduction: After the power density of the motor is increased, the volume is reduced by 10%-20% under the same torque specification, which alleviates the installation pressure of the compact space of the construction machinery; ③ Reduction of the whole life cycle cost: Based on the comprehensive calculation of motor procurement cost and installation and maintenance cost, the total cost can be reduced by 12%-25%.

[0063] (2) Dynamically optimize operating efficiency and improve energy utilization. Specifically: ① Load-efficiency coordination: Match high load periods with the high efficiency zone of the motor (usually 75%-90% of rated torque) through overload spectrum arrangement, so that the overall system efficiency is improved by 8%-15% (taking a permanent magnet synchronous motor as an example, the average efficiency in the traditional mode is 82%, and it can reach 89% after optimization); ② Low load loss suppression: Avoid the motor from running in the low efficiency zone (<40% of rated load) for a long time, reduce the ineffective energy consumption caused by copper loss and iron loss, and reduce the annual power consumption by 10%-20% in typical scenarios.

[0064] (3) Enhance the adaptability to operating conditions and extend the service life of equipment. Dynamic thermal boundary protection is adopted, specifically: the overload ratio is adjusted based on real-time heat dissipation conditions (such as cooling system efficiency and ambient temperature) to ensure that the winding temperature rise is ≤80% of the allowable value of the insulation class (for example, the H-class insulation limit is 180°C, and the actual control target is ≤150°C), and the service life is extended by 20%-30%.

[0065] (4) The project has strong scalability and is compatible with multiple application scenarios. Specifically: ① Standardized classification rules: Load spectrum classification parameters (such as peak coefficient and duty cycle) can be adapted to various engineering machinery such as excavators, cranes, and port machinery; ② Safety fallback mechanism: Multi-level protection strategies (temperature rise warning, current gradient limit, emergency shutdown) ensure the robustness of overload control and the fault response time is ≤50ms.

[0066] (5) Theoretical calculation method for motor overload temperature rise, which can quickly assess the feasibility of the initial motor scheme. Specifically, by establishing the motor thermal balance equation, the temperature theoretical calculation formula can be used to achieve rapid preliminary verification, avoiding unnecessary cost and time investment in the initial stage of scheme design by relying on simulation technology and bench tests, and improving the usability of the initial method of motor selection and design.

[0067] Example 2: This embodiment provides a dynamic matching device for an electric drive transmission system based on load spectrum drive, including: The data acquisition module is used to obtain load spectrum data based on the operating conditions of the electric drive system and the fatigue work cycle table of the construction machinery. The load spectrum analysis module is used to analyze load spectrum data and outputs a cyclic load spectrum of the motor throughout its entire life cycle and a cyclic loading table of the motor throughout its entire life cycle. The motor temperature rise theory processing module is used to establish a dynamic model of heat generation and heat dissipation power under load conditions based on the motor thermal balance equation, and to solve the theoretical temperature rise results of the motor at the working point of the cyclic loading table by combining the motor full life cycle cyclic loading table. The motor thermal simulation processing module is used to build a motor thermal simulation model, input the full life cycle loading table into the motor thermal simulation model to drive the motor to run, and output the motor thermal simulation temperature results. The electric drive system matching module combines the theoretical temperature rise results of the motor with the thermal simulation temperature results of the motor to dynamically adjust the thermal capacity coefficient and thermal resistance coefficient of the motor.

[0068] In this preferred embodiment, the load spectrum analysis module includes: The load spectrum classification submodule is used to classify the load spectrum data and output the dynamic characteristic parameters of the torque load spectrum. The motor overload judgment submodule screens and judges whether the motor is overloaded based on the motor overload rate and outputs the motor overload result; The cyclic load spectrum compilation submodule is used to extrapolate the extreme values ​​of the load spectrum and arrange the timing sequence. The output includes the cyclic load spectrum of the motor's entire life cycle and the cyclic loading table of the motor's entire life cycle.

[0069] Example 3: This embodiment provides a dynamic matching system for an electric drive transmission system, the dynamic matching system for the electric drive transmission system comprising: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the load spectrum-driven dynamic matching method for electric drive systems as described above.

[0070] Example 4: This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the dynamic matching method for an electric drive system based on load spectrum driving as described above.

[0071] Example 5: This embodiment provides a computer program product, including a computer program that, when executed by a processor, implements the dynamic matching method for an electric drive transmission system based on load spectrum driving as described above.

[0072] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention's specification and drawings under the inventive concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A dynamic matching method for an electric drive transmission system based on load spectrum driving, characterized in that, Includes the following steps: Step S1: Load spectrum acquisition of the transmission system, specifically: obtain load spectrum data based on the operating conditions of the electric drive system and the fatigue working cycle table of the engineering machinery; Step S2, load spectrum analysis, specifically: based on the load spectrum data obtained in step S1, perform load spectrum classification, motor overload applicability judgment and cyclic load spectrum compilation, and output the cyclic load spectrum of the motor throughout its entire life cycle and the cyclic loading table of the motor throughout its entire life cycle. Step S3: Obtain the theoretical temperature rise result of the motor. Specifically, based on the motor thermal balance equation, establish a dynamic model of heat generation and heat dissipation power under load conditions; input parameters include the motor's thermal capacity coefficient, the motor's thermal resistance coefficient, and the ambient temperature; map the operating points of the motor's full life cycle cyclic loading table obtained in step S2 to the motor MAP to find the power loss at the corresponding points; solve for the theoretical temperature rise result of the motor at the operating points of the cyclic loading table. To obtain the motor thermal simulation temperature results, specifically: construct a motor thermal simulation model; input the full life cycle loading table obtained in step S2 into the motor thermal simulation model, drive the motor to run, and output the motor thermal simulation temperature results; Step S4: Based on the theoretical temperature rise result of the motor obtained in step S3 and the temperature result of the motor thermal simulation, dynamically adjust the thermal capacity coefficient and the thermal resistance coefficient of the motor. The final outputs are the thermal capacity coefficient and thermal resistance coefficient of the motor.

2. The dynamic matching method for an electric drive transmission system based on load spectrum driving according to claim 1, characterized in that, In step S1: Operating conditions for electric drive systems include road type, terrain, traffic conditions, driving style, load weight, and equipment usage type; The fatigue work cycle table for construction machinery is derived from the operating conditions of the electric drive system and the working cycle of the equipment. The load spectrum data includes the torque and speed of the drive shaft.

3. The dynamic matching method for an electric drive transmission system based on load spectrum driving according to claim 2, characterized in that, Torsional strain is tested using strain gauges mounted on the drive shaft. The measured torsional strain is then calibrated using strain-torque to obtain the torque of the drive shaft. A photoelectric speed sensor is used to test the rotational speed of the drive shaft to obtain the rotational speed of the drive shaft.

4. The dynamic matching method for an electric drive transmission system based on load spectrum driving according to claim 1, characterized in that, In step S2, the load spectrum classification specifically involves extracting the dynamic characteristic parameters of the torque load spectrum. These dynamic characteristic parameters include: time-domain indicators, such as peak torque, mean torque, volatility, and duration; and frequency-domain indicators, such as the energy concentration frequency band and the impact response frequency.

5. The dynamic matching method for an electric drive transmission system based on load spectrum driving according to claim 4, characterized in that, The load spectrum can be categorized into steady torque spectrum, short-term overload torque spectrum, periodic fluctuation torque spectrum, stable fluctuation torque spectrum, and continuous fluctuation load spectrum.

6. The dynamic matching method for an electric drive transmission system based on load spectrum driving according to claim 4, characterized in that, The specific steps for determining the applicability of the motor to overload in step S2 are as follows: Motor overload rate refers to the percentage by which the actual operating load of a motor exceeds its rated load, i.e., motor overload rate = peak torque required by the load spectrum / rated torque of the motor configuration; When the peak torque required by the load spectrum is less than or equal to the rated torque of the motor, the motor overload rate is 1, and there is no overload. When the peak torque required by the load spectrum is greater than the rated torque of the motor, the motor overload rate is greater than 1, indicating overload.

7. The dynamic matching method for an electric drive transmission system based on load spectrum driving according to claim 6, characterized in that, The cyclic load spectrum compilation is specifically as follows: based on the rainflow counting method and extreme value statistics theory, the load frequency and amplitude are synchronously extrapolated and the overload multiple is adjusted; according to the time-frequency characteristics of the load spectrum, the overload period is inserted into the full life cycle standard cyclic spectrum to form the set overload test verification spectrum, and the output includes the full life cycle cyclic load spectrum of the motor and the full life cycle cyclic loading table of the motor.

8. The dynamic matching method for an electric drive transmission system based on load spectrum driving according to any one of claims 1-7, characterized in that, In step S3, the operating points of the motor's full life cycle cyclic loading table obtained in step S2 are mapped to the motor MAP to find the power loss at the corresponding point. The standard solution is as follows: ； in: for The temperature rise of the motor relative to the ambient temperature at any given time; Ambient temperature; The thermal capacity coefficient of the motor; The thermal resistance coefficient of the motor; This represents the power loss value of the motor. , This refers to the input electrical power of the motor. The output mechanical power of the motor. The efficiency at the motor's operating point; For time.

9. The dynamic matching method for an electric drive transmission system based on load spectrum driving according to claim 8, characterized in that, In step S4, the dynamic adjustment of the motor's thermal capacity coefficient and thermal resistance coefficient based on the theoretical temperature rise result and the motor thermal simulation temperature result obtained in step S3 is specifically to ensure that the deviation rate between the theoretical temperature rise result and the motor thermal simulation temperature result is <5%.

10. A dynamic matching device for an electric drive transmission system based on load spectrum driving, characterized in that, include: The data acquisition module is used to obtain load spectrum data based on the operating conditions of the electric drive system and the fatigue work cycle table of the construction machinery. The load spectrum analysis module is used to analyze load spectrum data and outputs a cyclic load spectrum of the motor throughout its entire life cycle and a cyclic loading table of the motor throughout its entire life cycle. The motor temperature rise theory processing module is used to establish a dynamic model of heat generation and heat dissipation power under load conditions based on the motor thermal balance equation, and to solve the theoretical temperature rise results of the motor at the working point of the cyclic loading table by combining the motor full life cycle cyclic loading table. The motor thermal simulation processing module is used to build a motor thermal simulation model, input the full life cycle loading table into the motor thermal simulation model to drive the motor to run, and output the motor thermal simulation temperature results. The electric drive system matching module combines the theoretical temperature rise results of the motor with the thermal simulation temperature results of the motor to dynamically adjust the thermal capacity coefficient and thermal resistance coefficient of the motor.

11. The dynamic matching device for an electric drive transmission system based on load spectrum driving according to claim 7, characterized in that, The load spectrum analysis module includes: The load spectrum classification submodule is used to classify the load spectrum data and output the dynamic characteristic parameters of the torque load spectrum. The motor overload judgment submodule screens and judges whether the motor is overloaded based on the motor overload rate and outputs the motor overload result; The cyclic load spectrum compilation submodule is used to extrapolate the extreme values ​​of the load spectrum and arrange the timing sequence. The output includes the cyclic load spectrum of the motor's entire life cycle and the cyclic loading table of the motor's entire life cycle.

12. A dynamic matching system for an electric drive transmission system, characterized in that, The electric drive system dynamic matching system includes: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the load spectrum-driven dynamic matching method for electric drive systems as described in any one of claims 1-11.

13. A computer-readable storage medium storing a computer program, characterized in that, When executed by the processor, the program implements the dynamic matching method for electric drive systems based on load spectrum driving as described in any one of claims 1-11.

14. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the dynamic matching method for an electric drive system based on load spectrum drive as described in any one of claims 1-11.

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