High-efficiency heat dissipation system of small high-power direct-drive motor and control method of high-efficiency heat dissipation system

Abstract

The invention discloses an efficient heat dissipation system of a small high-power direct-drive motor and a control method of the efficient heat dissipation system, and relates to a motor heat dissipation technology. The system comprises a hybrid heat dissipation assembly, a multi-source data acquisition module, a state prediction module and an optimization control module, the mixed heat dissipation assembly improves the heat dissipation efficiency through cooperation of air cooling and liquid cooling; the multi-source data acquisition module acquires motor temperature, environmental parameters and flight task data in real time, and the state prediction module constructs a dynamic heat dissipation model in combination with flight tasks and meteorological data to predict a future motor temperature change trend; and the optimization control module is used for dividing three heat dissipation modes of conventional heat dissipation, early warning heat dissipation and emergency heat dissipation based on a temperature prediction result, dynamically optimizing the rotating speed of the fan and the liquid cooling flow through a particle swarm algorithm, and realizing multi-target balance among temperature safety, energy consumption and life loss. The system solves the problems of poor environmental adaptability, control lag and high energy consumption of a traditional heat dissipation system, and has the advantages of dynamic heat dissipation efficiency improvement, predictive control and closed-loop life protection.

Description

TECHNICAL FIELD

[0001] The application relates to a motor heat dissipation technology, in particular to a high-efficiency heat dissipation system of a small-sized high-power direct-drive motor and a control method thereof. BACKGROUND

[0002] Electric fixed-wing unmanned aerial vehicles are widely used in people's livelihood fields, among which, motors are core components determining performance; researching and developing high-performance small-sized special motors is the only way to promote the development of the unmanned aerial vehicle industry; currently, the pain points of the motor include large self-weight, small current and low efficiency, which leads to insufficient power of the unmanned aerial vehicle and short flight range and other poor performance conditions; in order to change this situation, it is necessary to increase the magnetic flux density of the motor in a limited space, thereby increasing the power; However, the increase of the power will inevitably lead to severe heat dissipation challenges in the high-speed flight maneuvering process of the unmanned aerial vehicle; the existing heat dissipation system often dissipates heat in a single air cooling or liquid cooling manner, and the heat dissipation efficiency is low; and the existing heat dissipation system control strategy often adjusts the heat dissipation parameters in a real-time monitoring and fixed threshold corresponding manner, without considering the influence of the nonlinear heat dissipation environment in the high-altitude flight process on the heat dissipation efficiency, and lacking comprehensive consideration of the heat dissipation energy consumption and the motor life in order to improve the endurance and the motor life. Therefore, we provide a high-efficiency heat dissipation system of a small-sized high-power direct-drive motor and a control method thereof. SUMMARY

[0003] The application aims to provide a high-efficiency heat dissipation system of a small-sized high-power direct-drive motor and a control method thereof to solve the above problems.

[0004] The application can be implemented by the following technical scheme: a high-efficiency heat dissipation system of a small-sized high-power direct-drive motor, comprising: a hybrid heat dissipation component module, comprising an air cooling component driven by a heat dissipation fan and a liquid cooling component composed of a micro circulating pump and a heat exchanger; A multi-source data acquisition module is integrated with a temperature measuring instrument, an air pressure sensor, an air speed sensor and a flowmeter, and is used for acquiring the motor winding temperature, the cooling liquid inlet and outlet temperature, the air speed and the cooling liquid flow in real time, and acquiring the meteorological environment parameters through a communication mode; A data storage module is used for storing the real-time collected data, and a flight task file and a preset parameter threshold are preloaded in the data storage module; A state prediction module is used for predicting the environmental temperature, the motor demand power and the heat generation in a future time window based on the flight task file and the real-time meteorological data, so as to construct a dynamic heat dissipation model containing air cooling and liquid cooling, and predict the motor winding temperature through iterative calculation; The optimization control module selects a heat dissipation mode based on the real-time monitored temperature and the predicted motor winding temperature, determines the weight size of three concerned items of temperature safety, heat dissipation energy consumption and motor life loss, constructs an optimization objective function according to the three concerned items and sets a constraint condition, adopts a particle swarm algorithm to solve the optimal solution of the heat dissipation fan power and the micro circulating pump power, generates a rotating speed and flow control instruction, and forms a closed loop control.

[0005] Further technical improvement of the application is that in the state prediction module, the calculation formula of the predicted demand power is: ; Wherein, is the power in the cruising state, represents a power correction function driven by the pitch angle and the acceleration , represents different task phase state parameters, which are 0 or 1, 0 represents that the UAV is not in the corresponding task phase, and 1 represents that the UAV is in the corresponding task phase, takes an integer value in 1~4, and from small to large, respectively represents the task states of climbing, cruising, landing and maneuvering; and .

[0006] Further technical improvement of the application is that the dynamic heat dissipation model is ; Wherein, the air cooling heat dissipation model is ; represents the air cooling convection heat transfer coefficient, , represents the air cooling convection heat transfer coefficient at zero altitude at the corresponding moment, , represents the Nusselt number under forced convection condition, represents the thermal conductivity coefficient of the corresponding air temperature under standard atmospheric pressure, and , represents the extension length of the shell of the motor; represents the effective air cooling heat dissipation area, represents the winding temperature and the ambient temperature at the corresponding moment; The liquid cooling heat dissipation model is ; Wherein, represents the liquid cooling flow at the corresponding moment, represents the specific heat capacity of the cooling liquid, represents the outlet temperature and the inlet temperature of the liquid cooling component.

[0007] Further technical improvement of the application is that the ambient temperature at the height H position is ; Wherein, represents the temperature at zero altitude, It represents the deceleration rate of temperature increase with altitude, and the altitude H is also determined according to the flight mission phase at the corresponding moment.

[0008] A further technical improvement of the present invention is that when time changes, the motor winding heats up and dissipates heat simultaneously, and the formula for iterative calculation and prediction of temperature is: ; In the future time period Divide the time into N steps to get a step size of , every time step, the temperature is updated and the temperature is calculated iteratively; Where C represents the thermal capacity of the motor, ; They are the motor efficiency and the drone propeller efficiency respectively.

[0009] A further technical improvement of the present invention is to optimize the heat dissipation mode selection process of the control module, including: when and When selecting the conventional cooling mode, the weight factors of temperature safety, heat dissipation energy consumption, and motor life loss are set as 、 、 ; when or When the warning trigger mode is selected, the attention weight factors of temperature safety, heat dissipation energy consumption, and motor life loss are set as follows: 、 、 ; when or , set the attention weight factors of temperature safety, heat dissipation energy consumption, and motor life loss respectively 、 、 ; in, 、 They represent the first-level warning temperature threshold and the second-level dangerous temperature threshold respectively.

[0010] A further technical improvement of the present invention is that the optimization objective function is: ; in, Represent the cooling fan power and the micro-circulation pump power respectively, which are optimization variables. is the life loss penalty coefficient; Constraints include: upper temperature limit constraint, ; Energy consumption constraints, E represents the remaining battery power; Power constraints, i.e. the power of the cooling fan and the power of the micro circulating pump do not exceed the rated maximum power; Stable cooling mode constraint, i.e. mode switching is not performed until at least one minute of continuous operation of different cooling modes.

[0011] The control method of the above cooling system comprises the following steps: Step one, real-time acquisition of motor operating state data, environmental parameters and flight task data through a multi-source data acquisition module; Step two, prediction of demand power and environmental parameters in the future time window, calculation of heat generation and dynamic heat dissipation, and iterative update of temperature prediction value; Step three, selection of cooling mode and determination of the size of the attention weight factor of the three attention items of temperature safety, cooling energy consumption and motor life loss in the corresponding mode, construction of an optimization objective function to solve the optimal solution of the cooling fan power and the micro circulating pump power, and generation of control instructions; Step four, update of environmental data and motor state parameters at the next time step and re-optimization to form a closed-loop control.

[0012] Compared with the prior art, the present application has the following beneficial effects: 1. The cooling system of the present application cooperates air cooling and liquid cooling, adjusts the fan speed and liquid cooling flow rate adaptively according to airspeed and altitude, and significantly improves the cooling efficiency in high-altitude low-pressure environment.

[0013] 2. The present application integrates flight task data and real-time weather information, accurately predicts future thermal load, constructs a dynamic cooling model, realizes "feedforward control" of the cooling system, and avoids temperature lag response.

[0014] 3. The present application selects different cooling modes according to different temperature states of the motor, and matches the corresponding weight size of temperature safety, cooling energy consumption and motor life loss, so as to reduce the cooling energy consumption and the life loss of the motor as much as possible while ensuring cooling, realize high-efficiency energy ratio cooling, and play a good protective role for the motor; 4. The present application also controls the duration when switching the cooling mode, avoids control oscillation caused by frequent switching, improves the system reliability and ensures the relative stable state of the cooling system. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to facilitate those skilled in the art to understand, the present application will be further described below with reference to the drawings.

[0016] Figure 1 The system block diagram of the present application; Figure 2The flow chart of the control method of the application is shown in the figure. DETAILED DESCRIPTION

[0017] In order to further illustrate the technical means and effects adopted by the application to achieve the predetermined application purposes, the specific embodiments, structures, features and effects according to the application are described in detail below in combination with the drawings and preferred embodiments.

[0018] Referring to Figure 1 The high-efficiency heat dissipation system of the small high-power direct-drive motor includes a hybrid heat dissipation component module, a multi-source data acquisition module, a state prediction module, an optimization control module and a data storage module.

[0019] The hybrid heat dissipation component module includes an air-cooled component and a liquid-cooled component. The air-cooled component adopts a centrifugal frequency-modulated fan installed at the tail of the motor shell and introduces external cooling air flow through a flow guide groove. The liquid-cooled component adopts a micro circulating pump to drive low-viscosity cooling liquid (such as ethylene glycol aqueous solution) to flow through a spiral flow channel arranged in the motor stator winding, and finally circulate in an external heat exchanger provided with multiple fins for heat exchange. The frequency-modulated fan and the micro circulating pump are both electrically driven. The multi-source data acquisition module is integrated with a temperature meter, an air pressure sensor, an air speed sensor, an altimeter, a Hall sensor and a flowmeter to acquire the current working condition of the motor, the winding temperature, the cooling liquid inlet and outlet temperature, the air pressure, the air speed and the cooling liquid flow in real time, and send the data to the data storage module in time sequence for storage. The data storage module also stores a flight mission file containing waypoint coordinates, altitude profiles and task phase markers. The task phase markers include climbing, cruising, landing and maneuvering states. The state prediction module first predicts the predicted state parameters at a future time according to the flight mission file combined with real-time weather data based on wireless communication Specifically, According to the waypoint coordinates, altitude profiles and task phase markers at the future time, the altitude data and the set flight speed can be directly obtained. Among them, T0 represents the temperature at sea level, T represents the decreasing rate of temperature with the increase of altitude, which is generally 6.5℃ / km. The predicted demand power of the motor in the future time window , Pc represents the power in the cruising state, P represents the power correction function driven by the pitch angle and the acceleration , wherein the pitch angle , (i=1,2,3,4) represent different task phase state parameters, taking 0 or 1, 0 representing that the UAV is not in the corresponding task phase, and 1 representing that the UAV is in the corresponding task phase, and .

[0020] The state prediction module associates the heat generated by the motor according to the predicted state parameters in the future period of time and constructs a heat dissipation model, specifically: According to the predicted demand power The input power of the motor is calculated , wherein are the motor efficiency and the UAV propeller efficiency, respectively; The heat loss power (i.e. the heat generated per unit time) of the motor is .

[0021] The heat dissipation model is constructed, and since the height, speed and temperature environment of the UAV in the air change, the heat dissipation capacity changes at time, so the model is a dynamic heat dissipation model, including dynamic air cooling heat dissipation and dynamic liquid cooling heat dissipation; For dynamic air cooling heat dissipation, forced convection is mainly used: The heat dissipation per unit time of the motor is ; wherein, represents the air cooling convection heat transfer coefficient, , represents the air cooling convection heat transfer coefficient at zero altitude at the corresponding time, , represents the Nusselt number under forced convection conditions, which can be calculated by the current airspeed, the gas movement viscosity under standard atmospheric pressure, the air density, etc. Here, no further description is made; represents the thermal conductivity coefficient of the corresponding air temperature under standard atmospheric pressure, and , represents the extension length of the motor shell; represents the effective air cooling heat dissipation area, represents the winding temperature and the environmental temperature at the corresponding time; For liquid cooling heat dissipation: The heat dissipation per unit time of the motor is ; wherein, represents the liquid cooling flow at the corresponding time, represents the specific heat capacity of the cooling liquid, represents the outlet temperature and the inlet temperature of the liquid cooling component; The total heat dissipation is ; Then the motor winding temperature change rate at a certain moment is Where C represents the motor heat capacity, which can be calibrated by experimental measurement under the determined motor structure.

[0022] The time interval from the current time to a future time is divided into N time steps, with a step size of Thus, the temperature is updated every time step, and the temperature is iteratively calculated to predict the motor winding temperature at a certain future time.

[0023] The optimization control module optimizes and controls the working parameters of the air-cooled component and the liquid-cooled component based on the real-time monitoring and prediction results of the motor winding temperature, ensures the heat dissipation effect, reduces energy consumption, and reduces the loss of motor life. First, the decision rules of the motor hybrid heat dissipation component module and the corresponding heat dissipation modes under the rules are formulated to balance the relationship between the motor winding temperature safety, the heat dissipation component energy consumption, and the motor life: The first-level warning temperature threshold and the second-level dangerous temperature threshold are preset in the data storage module, and ; The optimization control module sets the heat dissipation modes with different priorities of attention to different optimization directions, including the following cases: (1) Conventional cooling mode This cooling mode satisfies and , so the motor winding temperature is within the safe temperature in the predictable future time, and the focus is on the heat dissipation energy consumption and the life loss, and the attention weight factors of temperature safety, heat dissipation energy consumption, and motor life loss are set to , , respectively.

[0024] (2) Warning triggering mode This cooling mode satisfies or , which indicates that the motor winding temperature triggers a warning in the predictable future time, and the focus is on the motor safety and energy consumption, and the attention weight factors of the three are set to , , respectively.

[0025] (3) Emergency cooling mode This cooling mode satisfies or ​​​, it means that the motor winding temperature will face the risk of temperature runaway in the foreseeable future, so the focus should be on motor safety. At this time, the attention weight factors of the three are set as 、 、 .

[0026] Secondly, we construct an optimization objective function for motor safety, heat dissipation energy consumption, and life loss: ; in, Represent the cooling fan power and the micro-circulation pump power respectively, which are optimization variables; is the life loss penalty coefficient, which is generally between 0.08 and 2.1, and increases with the increase of the total working time of the motor. Indicates the magnitude of temperature fluctuations that affect the life of the motor; Constraints include: Upper temperature limit constraint, When the temperature exceeds the upper limit, the task cannot continue to execute in order to protect the motor. It is necessary to jump directly to the motor control program to reduce the motor power for cooling.

[0027] Energy consumption constraints, , E represents the remaining battery power; Power constraints, that is, the power of the cooling fan and the micro-circulation pump must not exceed the rated maximum power; Cooling mode stability constraint, that is, different cooling modes must work continuously for at least one minute before switching modes.

[0028] Particle swarm optimization is used to find the optimal solution for cooling fan power and micro-circulation pump power. , and then the fan speed and liquid cooling flow rate at the corresponding power can be calculated based on the optimal solution power, and the hybrid heat dissipation component module is controlled according to the obtained fan speed and liquid cooling flow rate.

[0029] After the optimization adjustment control instruction corresponding to the current time step is issued, at the beginning of the next time step, the heat dissipation mode is reselected and the optimal solution is obtained based on the latest motor status data and the predicted data within a certain period of time in the future. The instruction is issued to enter a new optimization cycle. The length of the optimization cycle corresponds to the length of the time step. It should be noted that when the heat dissipation mode of the new optimization cycle is different from that of the previous cycle, it is necessary to wait for its heat dissipation mode to last for at least one minute before switching.

[0030] like Figure 2 As shown, the method for controlling heat dissipation of a motor based on the above heat dissipation system includes the following steps: Step one, real-time collection of winding temperature, cooling liquid inlet and outlet temperature, air speed, cooling liquid flow rate of the motor and real-time meteorological data of the flight airspace by the multi-source data collection module and storage to the data storage module, at the same time, setting flight task file and related parameter threshold in the data storage module, including first level warning temperature threshold, second level warning temperature threshold, etc. Step two, S21, the state prediction module predicts the predicted demand power in the future time window according to the flight task file, combined with the pitch angle and acceleration ; at the same time, the input power of the motor is calculated according to the predicted demand power, and then the heat generation per unit time is obtained; S22, constructing the air cooling heat dissipation model based on the flight parameters and environmental parameters, and constructing the liquid cooling heat dissipation model based on the cooling liquid flow rate and the inlet and outlet temperature; S23, calculating the corresponding temperature change rate according to the range time heat generation and total heat dissipation of the motor at a certain moment, and then constructing the temperature prediction iteration model to obtain the motor winding temperature in the future time.

[0031] Step three, the optimization control module selects the corresponding heat dissipation mode according to the size comparison of the predicted temperature and the first level warning temperature threshold, the second level danger temperature threshold and the temperature change rate, so as to determine the distribution weight size of the attention weight factor of the temperature safety, heat dissipation energy consumption and motor life loss three attention items; Constructing the multi-objective optimization function about temperature safety, heat dissipation energy consumption and motor life loss and setting multiple constraint conditions, using particle swarm algorithm to solve the optimal solution, and using the optimal solution for optimization control in the corresponding optimization period; Step four, after the optimization adjustment control instruction corresponding to the current time step is issued, the state prediction result is updated at the beginning of the next time step, and the heat dissipation parameters are re-optimized, so as to form a closed loop control.

[0032] The above is only the preferred embodiment of the present application, not any form of limitation on the present application, although the present application has been disclosed as above with the preferred embodiment, however, it is not intended to limit the present application, any person skilled in the art, without departing from the technical solution range of the present application, can make some changes or modifications to the above disclosed technical content to make equivalent embodiments with equivalent changes, but as long as it does not deviate from the technical solution content of the present application, any simple modification, equivalent change and modification of the above embodiment according to the technical essence of the present application, all still belong to the range of the technical solution of the present application.

Claims

1. An efficient heat dissipation system for a small, high-power direct-drive motor, characterized in that: include: A hybrid cooling component module, including an air cooling component driven by a cooling fan and a liquid cooling component consisting of a micro-circulation pump and a heat exchanger; The multi-source data acquisition module integrates a temperature meter, air pressure sensor, airspeed sensor, and flow meter to obtain real-time motor winding temperature, coolant inlet and outlet temperatures, airspeed, and coolant flow, and obtains meteorological environmental parameters through communication. A data storage module is used to store real-time collected data and is preloaded with flight mission files and preset parameter thresholds; The state prediction module predicts the ambient temperature, motor power demand, and heat generation within a future time window based on flight mission files and real-time meteorological data. This module then builds a dynamic cooling model that includes both air and liquid cooling, and uses iterative calculations to predict motor winding temperature. The optimization control module selects the heat dissipation mode based on the real-time temperature monitoring and predicted motor winding temperature, determines the weights of the three focus items: temperature safety, heat dissipation energy consumption, and motor life loss, constructs the optimization objective function and sets constraints based on the three focus items, uses the particle swarm algorithm to solve the optimal solution for the cooling fan power and the micro-circulation pump power, generates speed and flow control instructions, and forms a closed-loop control.

2. The high-efficiency heat dissipation system for a small-sized high-power direct-drive motor according to claim 1, characterized in that: In the state prediction module, the calculation formula for predicting required power is: ; in, is the power in cruise state, Indicated by the pitch angle and acceleration The power correction function of the drive, Indicates the status parameters of different mission stages, which can be 0 or 1. 0 means the drone is not in the corresponding mission stage, and 1 means the drone is in the corresponding mission stage. Take integer values ​​between 1 and 4, and from small to large they represent the mission states of climb, cruise, landing, and maneuvering respectively; and .

3. The high-efficiency heat dissipation system for a small-sized high-power direct-drive motor according to claim 1, characterized in that: The dynamic heat dissipation model is ; Among them, the air cooling model is ; represents the air-cooled convection heat transfer coefficient, , It represents the wind cooling convection heat transfer coefficient at zero altitude at the corresponding time, , represents the Nusselt number under forced convection conditions, represents the thermal conductivity of air at standard atmospheric pressure, and , Indicates the extended length of the motor housing; Indicates the effective air cooling area. Indicates the winding temperature and ambient temperature at the corresponding moment; Liquid cooling model is ; in, Indicates the liquid cooling flow at the corresponding moment, represents the specific heat capacity of the coolant, Indicates the water outlet and inlet temperatures of the liquid cooling component.

4. The high-efficiency heat dissipation system for a small-sized high-power direct-drive motor according to claim 3, characterized in that: The ambient temperature at height H is ; in, represents the temperature at zero altitude, It represents the deceleration rate of temperature increase with altitude, and the altitude H is also determined according to the flight mission phase at the corresponding moment.

5. The high-efficiency heat dissipation system for a small-sized high-power direct-drive motor according to claim 3, characterized in that: When time changes, the motor winding heats up and dissipates heat simultaneously. The formula for iterative calculation and prediction of temperature is: ; In the future time period Divide the time into N steps and get the step length as , every time step, the temperature is updated and the temperature is calculated iteratively; Where C represents the thermal capacity of the motor, ; They are the motor efficiency and the drone propeller efficiency respectively.

6. The high-efficiency heat dissipation system for a small-sized high-power direct-drive motor according to claim 5, characterized in that: The heat dissipation mode selection process of the optimization control module includes: when and When selecting the conventional cooling mode, the weight factors of temperature safety, heat dissipation energy consumption, and motor life loss are set as 、 、 ; when or When the warning trigger mode is selected, the attention weight factors of temperature safety, heat dissipation energy consumption, and motor life loss are set as follows: 、 、 ; when or , set the attention weight factors of temperature safety, heat dissipation energy consumption, and motor life loss respectively 、 、 ; in, 、 They represent the first-level warning temperature threshold and the second-level dangerous temperature threshold respectively.

7. The high-efficiency heat dissipation system for a small-sized high-power direct-drive motor according to claim 6, characterized in that: The optimization objective function is: ； in, Represent the cooling fan power and the micro-circulation pump power respectively, which are optimization variables. is the life loss penalty coefficient; Constraints include: upper temperature limit constraint, ; Energy consumption constraints, , E represents the remaining battery power; Power constraints, that is, the power of the cooling fan and the micro-circulation pump must not exceed the rated maximum power; Cooling mode stability constraint, that is, different cooling modes must work continuously for at least one minute before switching modes.

8. A method for controlling a heat dissipation system according to claim 1-7, characterized in that: The steps include: Step 1: Collect motor working status data, environmental parameters and flight mission data in real time through a multi-source data acquisition module; Step 2: Predict the required power and environmental parameters in the future time window, calculate the heat generation and dynamic heat dissipation, and iteratively update the temperature prediction value; Step 3: Select a cooling mode and determine the weight factors of the three key items of concern: temperature safety, cooling energy consumption, and motor life loss. Build an optimization objective function to find the optimal solution for cooling fan power and micro-circulation pump power, thereby generating control instructions. Step 4: Update the environmental data and motor state parameters at the next time step and re-optimize to form a closed-loop control.

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