An IPM module temperature adaptive derating control method and system based on a sliding mode control

Abstract

The application discloses an IPM module temperature adaptive derating control method and system based on a sliding mode control. In the application, the boundary layer formed by a saturation function and the rate limitation jointly act, so that the derating coefficient continuously changes with time and does not appear stepwise jump. Compared with the large speed fluctuation caused by the traditional fuzzy control, the method can limit the speed fluctuation in a small range, thereby significantly inhibiting the speed mutation. The consistent derating performance can be maintained when the environmental temperature changes in a large range. Whether in a cold state or a hot state, the false triggering and response lag can be avoided, so that the module temperature stably converges in a safe range. By providing a configurable parameter group, the same sliding mode control framework can be adapted to various application scenarios such as air conditioner indoor units, outdoor fans, compressors and automobile water pumps, so that the development and transplantation cost of the control algorithm is significantly reduced.

Description

Technical Field

[0001] This invention belongs to the field of motor drive control technology, specifically a temperature adaptive derating control method and system for IPM modules based on sliding mode control. Background Technology

[0002] In motor drive systems, the IPM module serves as the core of power conversion, and its internal junction temperature directly affects device lifespan and system safety. To prevent overheating damage, existing technologies typically employ a temperature derating strategy: when the temperature detected by the IPM's internal NTC sensor approaches its upper limit (e.g., 125°C), the output power is reduced or the motor speed is limited to decrease module current and internal power consumption.

[0003] For example, patent CN121618918A discloses a method for controlling motor over-temperature derating. This method determines the vehicle's operating conditions by collecting real-time parameters such as motor temperature, torque, and speed, and dynamically adjusts the motor's electric / generating capacity when temperature derating control is initiated. While this solution achieves dynamic derating based on operating conditions, its core logic is a discrete decision-making method based on "operating condition judgment + rule mapping," without employing a continuous feedback control law. Therefore, it may still exhibit response lag or over-adjustment when the ambient temperature fluctuates significantly.

[0004] However, existing technologies face the following specific technical problems in practical applications:

[0005] (1) The core contradiction between response lag and sudden speed change: In scenarios where the IPM is built into the motor body, the module dissipates heat through the motor end cover, resulting in a very large system heat capacity. The fixed temperature threshold of traditional solutions cannot adapt to this drift: if the threshold is set too low, derating will be falsely triggered in cold conditions; if the threshold is set too high, the response will be severely lagging in hot conditions, and once the temperature approaches the upper limit, the controller can only drastically reduce the duty cycle to "brake" the system, resulting in a precipitous drop in speed. This sudden speed change can cause noise, mechanical shock, and even system instability in applications such as air conditioner indoor units, air conditioner outdoor fans, compressors, and automotive water pumps.

[0006] (2) Fuzzy control, but its control accuracy is limited by the resolution of the rule table. When the temperature is really close to the upper limit, fuzzy control has often missed the best adjustment window.

[0007] (3) The thermal system of IPM has large inertia and large hysteresis characteristics, and the large range of changes in ambient temperature is equivalent to a continuous "external disturbance". The integral term of PID is prone to cumulative error under such slow time-varying disturbance, resulting in overshoot or steady-state error. Summary of the Invention

[0008] The purpose of this invention is to provide a temperature adaptive derating control method and system for IPM modules based on sliding mode control in order to solve the problems mentioned above.

[0009] The technical solution adopted in this invention is as follows: A temperature adaptive derating control method for an IPM module based on sliding mode control, comprising the following steps:

[0010] S1: The temperature is acquired by the built-in NTC of the IPM, converted by the ADC, and then filtered by a first-order low-pass filter with a filter coefficient of 0.2~0.3. The filtered temperature is then output to S3.

[0011] S2: Dynamically adjust the target temperature based on the estimated ambient temperature. The rated target temperature is 115~118℃, the reference ambient temperature is 25℃, the adaptive coefficient is 0.3~0.4, the lower limit is 105℃, and the output is sent to S3.

[0012] S3: The error between the target temperature and the filtered temperature is used to construct a sliding surface based on the error change rate, so that the controller can predict the temperature rise trend and output to S4 and S5.

[0013] S4: Use a saturation function to replace the sign function to design a smoothing reaching law. The boundary layer thickness is 3~5℃, which makes the output change continuously and provides a smoothing basis for S5.

[0014] S5: Map the sliding surface to a derating factor. If the value is greater than zero, take zero. If the value is less than or equal to zero, map it with a slope of 0.08~0.15 and limit the amplitude. Then limit the change of 0.008~0.015 per cycle and output it to S6.

[0015] S6: The derating factor is multiplied by the speed loop output to obtain the final duty cycle. The minimum duty cycle is set to 5%. The IPM is driven by the current loop to achieve temperature convergence and smooth speed.

[0016] In a preferred embodiment, in step S1, the temperature and voltage signal is acquired by the NTC sensor built into the IPM module and converted into a temperature value by the ADC. A first-order low-pass filter is used to suppress NTC noise.

[0017]

[0018] in, This is the temperature value after ADC conversion in the current cycle; This is the output of the current cycle's filter; This is the output of the previous cycle's filter; These are the filter coefficients, with typical values ​​taking... Filtered The input is S3, and the target temperature output from S2 is... This creates a temperature error.

[0019] In a preferred embodiment, in step S2, based on the estimated ambient temperature value... Dynamically adjust the target temperature of the sliding mode controller:

[0020]

[0021] in, For the rated target temperature, take ; For reference, ambient temperature was taken. ; For adaptive coefficients, typical values ​​are taken as follows: ; This indicates that a negative correction is only performed when the ambient temperature is higher than the reference value; The lower limit protection value is taken as .

[0022] In a preferred embodiment, in step S2, the ambient temperature estimation is performed by an ambient temperature estimation module, which can be implemented in two ways, specifically including:

[0023] Method 1: Use the first valid NTC reading as the initial value during motor startup. The initial value is then updated recursively to the current IPM temperature filter value every 30 minutes using a fixed time constant.

[0024] Method 2: Install a low-cost NTC for direct measurement near the motor end cover.

[0025] Output to S3 to adjust the target temperature according to the ambient temperature drift.

[0026] In a preferred embodiment, step S3, specifically the construction of the sliding surface, includes:

[0027] Define temperature error:

[0028]

[0029] Temperature error change rate:

[0030]

[0031] Where e[k] is the temperature error of the current control cycle; e[k-1] is the temperature error of the previous cycle; To control the cycle.

[0032] Constructing the sliding surface:

[0033] Where λ is the sliding surface coefficient, λ>0, and a typical value is taken as... The sliding surface simultaneously incorporates temperature error and temperature change rate, enabling the controller to "anticipate" temperature rise trends. When the temperature has not yet exceeded the limit but the temperature rise rate is rapid, SS changes in advance, triggering predictive derating. SS is output to S4 for smoothing approach law design and to S5 for derating factor mapping.

[0034] In a preferred embodiment, in step S4, the smooth reaching law design uses a saturation function instead of the sign function in traditional sliding mode control. The saturation function is:

[0035]

[0036] in, The boundary layer thickness is typically taken as... ; For the gain of the reaching law, Typical value Typical values ​​for k are: The saturation function provides a linear transition band near the sliding surface, allowing the control output to vary continuously within the boundary layer rather than through switching abrupt changes. This mathematically ensures the smoothness of the derating factor and avoids sudden changes in rotational speed. This step provides the basis for continuous control in calculating the derating factor of S5.

[0037] In a preferred embodiment, in step S5, the derating factor is calculated and the derating is limited.

[0038] Mapping sliding mode surface values ​​to derating factors:

[0039]

[0040] Where g is the derating slope gain, g>0, and a typical value is taken as... Adjust according to the module's thermal capacity.

[0041] In a preferred embodiment, applying a rate limit in step S5 includes:

[0042]

[0043] Where u[k] is the current cycle reduction coefficient; u[k-1] is the previous cycle reduction coefficient; The maximum change per control cycle, typically taken as... ;clamp indicates that The speed limit is set between upper and lower limits. The rate limit is the last line of defense to ensure smooth rotational speed; even slight fluctuations in the sliding mode controller output can be smoothed out. The final output derating coefficient u∈[0,1] to S6.

[0044] When adapting to different scenarios, the indoor unit of the air conditioner increases δ and decreases δ. To reduce noise; the outdoor fan of the air conditioner has reduced g and increased λ to resist mechanical impact.

[0045] In a preferred embodiment, in step S6, the derating factor u is related to the target duty cycle of the speed loop output. Multiplying these together gives the final PWM duty cycle applied to the IPM module:

[0046]

[0047] in, The target duty cycle for the speed loop output is given; u is the derating factor for the S5 output. The minimum duty cycle protection is set to 5% to prevent the motor from completely stopping. The speed loop and current loop use conventional PI control, and their outputs are not affected by the sliding mode controller structure; the sliding mode controller only "scales" the speed loop output through the derating factor u, seamlessly integrating into the existing control architecture. The IPM module is based on... The output of three-phase PWM drives the motor body, ensuring that the temperature stabilizes within a safe range while maintaining a smooth speed transition.

[0048] In a preferred embodiment, an IPM module temperature adaptive derating control system based on sliding mode control is characterized in that: the system uses the IPM module temperature adaptive derating control method based on sliding mode control as described in any one of claims 1 to 9 during operation, comprising: an ambient temperature estimation module, a sliding mode temperature derating controller, a speed loop PI controller, a current loop PI controller, an IPM module, a motor, and an NTC sensor.

[0049] The NTC sensor is built into the IPM module, which collects the module's temperature signal and outputs it to the sliding mold temperature derating controller.

[0050] The ambient temperature estimation module estimates the internal ambient temperature of the motor. The estimated ambient temperature is output to the sliding mode temperature derating controller, which is used to dynamically adjust the target temperature of the sliding mode controller. The module is implemented in the following ways:

[0051] Pure software solution: The first valid NTC reading is used as the starting point of the motor. The initial value is then updated recursively to the current IPM temperature filter value every 30 minutes using a fixed time constant.

[0052] Hardware-assisted solution: Install a low-cost NTC device near the motor end cover to directly measure the ambient temperature;

[0053] Sliding Mode Observer Enhancement Scheme: Utilize SMO to estimate motor parameters and then predict temperature rise trends.

[0054] The sliding mode temperature derating controller receives the filtered IPM temperature. and ambient temperature estimates Output depreciation coefficient The controller internally performs temperature signal acquisition and filtering, ambient temperature adaptive target temperature calculation, sliding mode surface construction, smoothing approach law design, derating factor calculation, and limiting. The derating factor u is multiplied by the target duty cycle output by the speed loop to obtain the final PWM duty cycle applied to the IPM module.

[0055] The speed loop PI controller uses conventional PI control and receives the derating factor u from the sliding mode temperature derating controller. Its output, multiplied by the derating factor u, is then input into the current loop. The speed loop output is unaffected by the sliding mode controller structure; the sliding mode controller only scales the speed loop output using the derating factor u.

[0056] The current loop PI controller uses conventional PI control, receives the signal after multiplying the speed loop output by the derating factor, and outputs a drive signal to the IPM module.

[0057] The IPM module receives the drive signal from the current loop and outputs a three-phase PWM to drive the motor body. The internal NTC sensor of the IPM module continuously collects the module temperature signal to form a closed-loop control.

[0058] The motor is driven by a three-phase PWM output from the IPM module, forming an IPM-embedded motor drive system.

[0059] The IPM module's internal NTC sensor collects the module's temperature signal and outputs it to the sliding mode temperature derating controller; the ambient temperature estimation module outputs the estimated ambient temperature value to the sliding mode temperature derating controller; the sliding mode temperature derating controller outputs the derating coefficient u to the speed loop; the speed loop output is multiplied by the derating coefficient and then drives the IPM module through the current loop; the IPM module outputs a three-phase PWM to drive the motor body.

[0060] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0061] 1. In this invention, the boundary layer formed by the saturation function and the rate limit work together to ensure that the derating coefficient changes continuously over time, without any abrupt jumps. Compared to the large speed fluctuations that are easily caused by traditional fuzzy control, this method can limit speed fluctuations to a smaller range, thereby significantly suppressing sudden speed changes. It maintains consistent derating performance even under large variations in ambient temperature. Whether in cold or hot conditions, it avoids false triggering and response lag, ensuring that the module temperature stabilizes within a safe range.

[0062] 2. In this invention, a temperature change rate is introduced into the sliding mode surface, enabling the controller to sense and predict temperature rise trends. When the load suddenly increases, derating can be triggered earlier than solutions relying solely on temperature thresholds, effectively preventing temperature overshoot. Sliding mode control is insensitive to parameter perturbations and external disturbances. Even if the radiator thermal resistance changes due to differences in installation processes, or if there are errors in the ambient temperature estimation, the controller can still automatically adjust the control quantity through a reaching law to maintain stable temperature convergence. By providing configurable parameter sets, the same sliding mode control framework can be adapted to various application scenarios such as air conditioner indoor units, outdoor fans, compressors, and automotive water pumps, significantly reducing the development and porting costs of control algorithms. Attached Figure Description

[0063] Figure 1 This is a schematic diagram illustrating the process principle of the present invention;

[0064] Figure 2 This is a system block diagram of the present invention. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0066] Reference Figure 1-2 ,

[0067] Example 1: Built-in driver for air conditioner indoor unit IPM

[0068] I. Application Scenarios and Hardware Configuration:

[0069] This embodiment applies to an indoor air conditioner unit. The motor has a rated power of 150W, and the IPM module (600V / 6A, MOSFET output) is integrated into the indoor unit body, dissipating heat through a metal end cover. The bus voltage is 310VDC, and the rated current is 0.5A. The IPM module integrates an NTC sensor for temperature monitoring. The system adopts an IPM-integrated motor drive architecture, meaning the IPM module is built into the motor body and dissipates heat through the motor end cover. In this scenario, the system has extremely high heat capacity. The internal ambient temperature of the motor during cold start is approximately 20~30℃, reaching 95℃ after 1~2 hours of operation. The end cover temperature can reach 80℃, and the air temperature near the end cover can reach 70℃. Therefore, a large range of ambient temperature fluctuations is the main characteristic of the operating condition.

[0070] II. Control Parameter Configuration:

[0071] This embodiment employs an IPM module temperature adaptive derating control method based on sliding mode control, with the following parameter configuration:

[0072] Rated target temperature: Tref_nominal =115℃;

[0073] Sliding surface coefficient: λ=1.2;

[0074] Boundary layer thickness: δ=4℃

[0075] Approach law gain: ε=0.15, k=5.0;

[0076] Derating slope gain: g=0.10;

[0077] Maximum change per control cycle: Δu max =0.012;

[0078] Adaptive coefficient: β = 0.35;

[0079] Reference ambient temperature: T amb_ref =25℃;

[0080] Filtering coefficient: α = 0.25;

[0081] III. Control System Composition:

[0082] The system includes: an ambient temperature estimation module, a sliding mode temperature derating controller, a speed loop PI controller, a current loop PI controller, an IPM module, a motor, and an NTC sensor built into the IPM module.

[0083] NTC sensor: Built into the IPM module, it collects the module temperature signal and outputs it to the sliding mold temperature derating controller.

[0084] Ambient temperature estimation module: Estimates the internal ambient temperature T of the motor. amb The output is sent to the sliding mode temperature derating controller. This embodiment uses a purely software solution: when the motor starts, the first valid NTC reading is used as the T value. amb The initial value is then updated recursively to the current IPM temperature value every 30 minutes.

[0085] Sliding mode temperature derating controller: Receives the filtered IPM temperature Tipm and the estimated ambient temperature T. amb The output deduction coefficient u∈[0,1] is given.

[0086] Speed ​​loop PI controller: It adopts conventional PI control, receives the derating factor u, and its output is multiplied by the derating factor and then input to the current loop.

[0087] Current loop PI controller: adopts conventional PI control, and outputs drive signals to the IPM module.

[0088] IPM module: Outputs three-phase PWM to drive the motor body, while the internal NTC continuously collects the module temperature, forming a closed loop.

[0089] The system architecture is as follows: the NTC sensor inside the IPM module collects the module's temperature signal and outputs it to the sliding mode temperature derating controller; the ambient temperature estimation module outputs the estimated ambient temperature value to the sliding mode temperature derating controller; the sliding mode temperature derating controller outputs the derating coefficient u to the speed loop; the speed loop output is multiplied by the derating coefficient and then drives the IPM module through the current loop; the IPM module outputs a three-phase PWM to drive the motor body.

[0090] IV. Implementation of Control Methods and Procedures:

[0091] S1: Temperature signal acquisition and filtering. Temperature and voltage signals are acquired via the built-in NTC sensor in the IPM module, converted to temperature values ​​by an ADC, and then a first-order low-pass filter is used to suppress NTC noise. In this embodiment, the filter coefficient is 0.25. The filtered IPM temperature is sent to S3, creating a temperature error with the target temperature output from S2.

[0092] S2: Ambient temperature adaptive target temperature calculation. The target temperature of the sliding mode controller is dynamically adjusted based on the estimated ambient temperature. In this embodiment, the rated target temperature is 115℃, the adaptive coefficient is 0.35, the reference ambient temperature is 25℃, and the lower limit protection value of the target temperature is 105℃. The estimated ambient temperature is provided by the ambient temperature estimation module: when the motor starts, the first valid reading of the NTC is used as the initial value of the ambient temperature, and then it is updated to the filtered value of the current IPM temperature every 30 minutes with a fixed time constant. The target temperature is output to S3.

[0093] S3: Sliding surface construction. A sliding surface is constructed based on the temperature error between the target temperature and the filtered IPM temperature, combined with the rate of change of this temperature error. In this embodiment, the sliding surface coefficient is 1.2. The sliding surface simultaneously incorporates both the temperature error and the rate of temperature change, enabling the controller to anticipate temperature rise trends. When the temperature has not yet exceeded the limit but the rate of temperature rise is rapid, the sliding surface changes in advance, triggering predictive derating. The sliding surface output is sent to S4 and S5.

[0094] S4: Smooth Approach Law Design. A saturated function is used to replace the sign function in traditional sliding mode control to design a smooth approach law. In this embodiment, the boundary layer thickness is 4°C, and the approach law gain is 0.15 and 5.0. The saturated function provides a linear transition band near the sliding surface, allowing the control output to change continuously within the boundary layer, rather than through switching abrupt changes. This mathematically ensures the smoothness of the derating coefficient and avoids sudden changes in rotational speed. This step provides the basis for continuous control in the derating coefficient calculation in S5.

[0095] S5: Derating Factor Calculation and Limiting. The sliding surface value is mapped to a derating factor. In this embodiment, when the sliding surface is greater than 0, the derating factor is 0; when the sliding surface is less than or equal to 0, it is mapped according to a derating slope gain of 0.10 and limited to no more than 1. A rate limit is further applied, with a maximum change of 0.012 per control cycle. The rate limit is the last line of defense to ensure smooth rotational speed; even if there are small fluctuations in the sliding mode controller output, they can be smoothed out. The final output derating factor is shown in S6.

[0096] S6: The derating factor is applied to the speed loop. The derating factor is multiplied by the target duty cycle of the speed loop output to obtain the final PWM duty cycle applied to the IPM module. In this embodiment, the minimum duty cycle protection is 5% to prevent the motor from stopping completely. The speed loop and current loop use conventional PI control, and their output is not affected by the sliding mode controller structure; the sliding mode controller only scales the speed loop output through the derating factor, seamlessly integrating into the existing control architecture. The IPM module outputs a three-phase PWM to drive the motor body according to the final duty cycle, ensuring that the temperature stabilizes within a safe range while maintaining a smooth speed transition.

[0097] V. Actual Measurement Results:

[0098] During cold start, the ambient temperature was 25℃, the target temperature was 115℃, the derating factor was 0, and the motor ran at full speed. After 90 minutes of operation, the ambient temperature rose to 85℃, and the target temperature adaptively decreased to approximately 94℃ (115−0.35×60). The derating factor slowly increased from 0 to 0.35, and the speed smoothly decreased from 2200rpm to approximately 1300rpm. The temperature stabilized around 115℃, without triggering the 125℃ hard protection. Compared with traditional fuzzy control, the speed fluctuation of this invention can be controlled within ±3% to ±8%, significantly suppressing sudden speed changes.

[0099] VI. Scene-specific adaptation instructions:

[0100] To address the core requirement of low noise in air conditioner indoor units, this embodiment employs methods such as increasing δ and decreasing Δu. max The parameters are emphasized. Specifically, δ=4℃, Δu max =0.012, by increasing the boundary layer thickness and reducing the change in the derating factor per cycle, the derating action is further smoothed, and noise is reduced. The same sliding mode control framework can be adapted to various application scenarios such as air conditioner outdoor fans, compressors, and automotive water pumps by adjusting the parameter groups.

[0101] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0102] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A temperature adaptive derating control method for an IPM module based on sliding mode control, characterized in that: Includes the following steps: S1: The temperature is acquired by the built-in NTC of the IPM, converted by the ADC and then filtered by a first-order low-pass filter with a filter coefficient of 0.2~0.

3. The filtered temperature is then output to S3. S2: Dynamically adjust the target temperature based on the estimated ambient temperature. The rated target temperature is 115~118℃, the reference ambient temperature is 25℃, the adaptive coefficient is 0.3~0.4, the lower limit is 105℃, and the output is sent to S3. S3: The error between the target temperature and the filtered temperature is used to construct a sliding surface based on the error change rate, so that the controller can predict the temperature rise trend and output to S4 and S5. S4: Use a saturation function to replace the sign function to design a smoothing reaching law. The boundary layer thickness is 3~5℃, which makes the output change continuously and provides a smoothing basis for S5. S5: Map the sliding surface to a derating factor. If the value is greater than zero, take zero. If the value is less than or equal to zero, map it with a slope of 0.08~0.15 and limit the amplitude. Then limit the change of 0.008~0.015 per cycle and output it to S6. S6: The derating factor is multiplied by the speed loop output to obtain the final duty cycle. The minimum duty cycle is set to 5%. The IPM is driven by the current loop to achieve temperature convergence and smooth speed.

2. The temperature adaptive derating control method for an IPM module based on sliding mode control according to claim 1, characterized in that: In step S1, the temperature and voltage signals are acquired by the NTC sensor built into the IPM module and converted into temperature values ​​by the ADC. A first-order low-pass filter is used to suppress NTC noise. in, This is the temperature value after ADC conversion in the current cycle; This is the output of the current cycle's filter; This is the output of the previous cycle's filter; These are the filter coefficients, with typical values ​​taking... ; after filtering The input is S3, and the target temperature output from S2 is... This creates a temperature error.

3. The temperature adaptive derating control method for an IPM module based on sliding mode control according to claim 1, characterized in that: In step S2, based on the estimated ambient temperature value Dynamically adjust the target temperature of the sliding mode controller: in, For the rated target temperature, take ; For reference, ambient temperature was taken. ; For adaptive coefficients, typical values ​​are taken as follows: ; This indicates that a negative correction is only performed when the ambient temperature is higher than the reference value; The lower limit protection value is taken as .

4. The temperature adaptive derating control method for an IPM module based on sliding mode control according to claim 1, characterized in that: In step S2, the ambient temperature estimation is performed by the ambient temperature estimation module, which has two implementation methods, specifically including: Method 1: Use the first valid NTC reading as the initial value during motor startup. The initial value is then updated recursively to the current IPM temperature filter value every 30 minutes using a fixed time constant. Method 2: Install a low-cost NTC for direct measurement near the motor end cover; Output to S3 to adjust the target temperature according to the ambient temperature drift.

5. The temperature adaptive derating control method for an IPM module based on sliding mode control according to claim 1, characterized in that: In step S3, the construction of the sliding surface specifically includes: Define temperature error: Temperature error change rate: Where e[k] is the temperature error of the current control cycle; e[k-1] is the temperature error of the previous cycle; To control the cycle; Constructing the sliding surface: Where λ is the sliding surface coefficient, λ>0, and a typical value is taken as... .

6. The temperature adaptive derating control method for an IPM module based on sliding mode control according to claim 1, characterized in that: In step S4, the smooth reaching law design uses a saturation function to replace the sign function in traditional sliding mode control; the saturation function is: in, The boundary layer thickness is typically taken as... ; For the gain of the reaching law, Typical value Typical values ​​for k are: .

7. The temperature adaptive derating control method for an IPM module based on sliding mode control according to claim 1, characterized in that: In step S5, the reduction factor is calculated and the limit is set. Mapping sliding mode surface values ​​to derating factors: Where g is the derating slope gain, g>0, and a typical value is taken as... Adjust according to the module's thermal capacity.

8. The temperature adaptive derating control method for an IPM module based on sliding mode control according to claim 1, characterized in that: In step S5, applying the rate limit includes: Where u[k] is the current cycle reduction coefficient; u[k-1] is the previous cycle reduction coefficient; The maximum change per control cycle, typically taken as... ;clamp indicates that The limits are set between the upper and lower bounds; the final output reduction coefficient u∈[0,1] to S6; When adapting to different scenarios, the indoor unit of the air conditioner increases δ and decreases δ. To reduce noise; the outdoor fan of the air conditioner has reduced g and increased λ to resist mechanical impact.

9. The temperature adaptive derating control method for an IPM module based on sliding mode control according to claim 1, characterized in that: In step S6, the derating factor u is related to the target duty cycle output by the velocity loop. Multiplying these together gives the final PWM duty cycle applied to the IPM module: in, The target duty cycle for the speed loop output is given; u is the derating factor for the S5 output; the minimum duty cycle protection is set to 5% to prevent the motor from completely stopping; the speed loop and current loop use conventional PI control, and their outputs are not affected by the sliding mode controller structure; the sliding mode controller only scales the speed loop output through the derating factor u, seamlessly integrating into the existing control architecture; the IPM module is based on... The output of three-phase PWM drives the motor body, ensuring that the temperature stabilizes within a safe range while maintaining a smooth speed transition.

10. A temperature adaptive derating control system for an IPM module based on sliding mode control, characterized in that: The system uses the sliding mode control-based IPM module temperature adaptive derating control method as described in any one of claims 1 to 9 during operation, including: an ambient temperature estimation module, a sliding mode temperature derating controller, a speed loop PI controller, a current loop PI controller, an IPM module, a motor, and an NTC sensor. The NTC sensor is built into the IPM module to collect the module temperature signal and output it to the sliding mode temperature derating controller. The ambient temperature estimation module estimates the internal ambient temperature of the motor. The estimated ambient temperature is output to the sliding mode temperature derating controller, which is used to dynamically adjust the target temperature of the sliding mode controller. The implementation methods of this module include: Pure software solution: The first valid NTC reading is used as the starting point of the motor. The initial value is then updated recursively to the current IPM temperature filter value every 30 minutes using a fixed time constant. Hardware-assisted solution: Install a low-cost NTC device near the motor end cover to directly measure the ambient temperature; Sliding Mode Observer Enhancement Scheme: Utilize SMO to estimate motor parameters and then predict temperature rise trends; The sliding mode temperature derating controller receives the filtered IPM temperature. and ambient temperature estimates Output depreciation coefficient The controller internally performs temperature signal acquisition and filtering, ambient temperature adaptive target temperature calculation, sliding mode surface construction, smoothing approach law design, derating factor calculation and limiting; the derating factor u is multiplied by the target duty cycle output by the speed loop to obtain the final PWM duty cycle applied to the IPM module. The speed loop PI controller uses conventional PI control and receives the derating factor u from the sliding mode temperature derating controller. Its output is multiplied by the derating factor u and then input into the current loop. The speed loop output is not affected by the structure of the sliding mode controller. The sliding mode controller only scales the speed loop output through the derating factor u. The current loop PI controller uses conventional PI control, receives the signal after multiplying the speed loop output by the derating factor, and outputs a drive signal to the IPM module. The IPM module receives the drive signal output from the current loop and outputs a three-phase PWM to drive the motor body; the NTC sensor inside the IPM module continuously collects the module temperature signal to form a closed-loop control. The motor is driven by a three-phase PWM output from the IPM module, forming an IPM-embedded motor drive system; The IPM module's internal NTC sensor collects the module's temperature signal and outputs it to the sliding mode temperature derating controller; the ambient temperature estimation module outputs the estimated ambient temperature value to the sliding mode temperature derating controller; the sliding mode temperature derating controller outputs the derating coefficient u to the speed loop; the speed loop output is multiplied by the derating coefficient and then drives the IPM module through the current loop; the IPM module outputs a three-phase PWM to drive the motor body.

Images