Intelligent driving cleaning method based on brushless direct current motor

Abstract

The present application relates to the technical field of automatic driving, in particular to a kind of intelligent driving cleaning method based on brushless DC motor.Electric machine and pump body integrated design, built-in heat dissipation channel;The heat dissipation channel is filled with phase change material, and the melting point of the phase change material is 50-65 ℃;Utilize intelligent controller to control gas-liquid mixed cleaning module, and the pump body cleaning mode is switched.The above-mentioned method is integrated by brushless DC motor, multi-mode intelligent cleaning and fault self-diagnosis mechanism, effectively improves sensor cleaning efficiency and system reliability, reduces the system misjudgment rate caused by sensor surface pollution.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving technology, and specifically to an intelligent driving cleaning method based on a brushless DC motor. Background Technology

[0002] Autonomous vehicles rely on sensors such as LiDAR and cameras to perceive their environment in real time. However, the surfaces of these sensors are easily contaminated by dust, rain, snow, and insects, leading to data distortion and even system failure. Existing cleaning systems mostly use brushed motors to drive water pumps, which suffer from low efficiency, short lifespan, and frequent maintenance. While some solutions use brushless motors, their complex structure, poor heat dissipation, and failure to fully integrate sensor status with dynamic adjustments to the cleaning strategy are problematic.

[0003] For example, the CN115743039A patent uses a fixed threshold cleaning strategy, which cannot adapt to complex environments; the US20220281420 patent uses an external heat dissipation structure, which is bulky and inefficient; the US10173646B1 patent uses a mechanical gas-liquid switching structure, which is slow to respond and prone to wear; moreover, the traditional PID control algorithm has a slow dynamic response and large torque fluctuations (>5%).

[0004] According to industry statistics, system misjudgments caused by sensor surface contamination account for 18.7% of autonomous driving accidents. Therefore, keeping sensor surfaces clean directly affects the safety of autonomous driving. Summary of the Invention

[0005] The purpose of this invention is to solve the above-mentioned problems by proposing an intelligent driving cleaning method based on a brushless DC motor.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A smart cleaning method based on a brushless DC motor is characterized by an integrated design of the motor and pump body with a built-in heat dissipation channel; the heat dissipation channel is filled with a phase change material with a melting point of 50-65℃; and an intelligent controller is used to control the gas-liquid mixing cleaning module to switch the pump body cleaning mode.

[0007] Preferably, the gas-liquid mixing cleaning module includes liquid injection and gas purging sub-modules, and the mode switching is realized by electromagnetic switching valve. The cleaning parameters are dynamically adjusted according to the pollution detection data of the sensor. The dynamic adjustment adopts a fuzzy PID algorithm combined with an LSTM machine learning model. The LSTM model predicts future pollution trends based on historical pollution detection data.

[0008] Preferably, the motor drive circuit supports a wide voltage input of 12V / 24V, adopts a sensorless FOC control algorithm, and combines an adaptive sliding mode observer to achieve stable operation in the full speed domain. The position estimation error of the adaptive sliding mode observer is less than 0.5°.

[0009] Preferably, the intelligent controller integrates a fault diagnosis module to monitor the motor voltage, current, temperature and temperature change rate in real time. When the temperature change rate exceeds 10℃ / s, an early warning is triggered, and when it exceeds 15℃ / s, the power supply is cut off.

[0010] Preferably, the pump body is equipped with a cleaning fluid tank, which has a built-in heater and an ultrasonic level sensor. The cleaning fluid is automatically heated in low-temperature environments, and the pump switches to gas-only cleaning when the level is low. The heater has a power of 50-100W and a heating rate of 2℃ / min.

[0011] Preferably, the pump body adopts a double-layer structure combining corrosion-resistant plastic and stainless steel. The corrosion-resistant plastic is PPS+30%GF, and the stainless steel is 316L. It communicates with the vehicle ECU via CAN bus, with an average power consumption of <5W and a standby power consumption of <0.5W.

[0012] The intelligent driving cleaning method based on a brushless DC motor proposed in this invention has the following advantages: 1. Integrated design of the brushless DC motor: The brushless DC motor (BLDC) and pump body are integrated into a single structure. The motor has a built-in heat dissipation channel, achieving active cooling through circulating cleaning fluid. The heat dissipation structure integrates a 0.5mm thick copper-based heat spreader on the motor housing, filled with paraffin phase change material (RT58) with a melting point of 58℃, which can control the motor temperature rise to within 20℃ within 5 seconds. SGS testing shows that after 30 minutes of continuous operation, the motor temperature is 35℃ lower than traditional air-cooled solutions. The drive circuit adopts a wide voltage input (12V / 24V adaptive) and combines it with a sensorless FOC control algorithm, achieving stable operation across the entire speed range through an adaptive sliding mode observer. Compared to traditional PID control, the dynamic response speed is improved by 30%, and torque ripple is reduced to below 1.2%.

[0013] 2. Multi-mode intelligent cleaning strategy: The system integrates liquid and gaseous dual cleaning modules, adopts dynamic cleaning decision-making, and uses lidar contamination detection: liquid cleaning is triggered by point cloud density analysis (point cloud occupancy rate within 10cm > 20%); camera contamination detection: gaseous purging is initiated based on image grayscale histogram analysis (brightness standard deviation < 15); environmental adaptation: cleaning parameters are optimized by fuzzy PID algorithm by combining parameters such as vehicle speed and ambient temperature, and LSTM model is introduced to predict contamination trends, achieving a water saving rate of up to 40%; mode switching mechanism: seamless switching between liquid (0.5-2MPa pressure adjustable) and gaseous (0.8-1.5MPa pressure adjustable) cleaning modes is achieved through the coordinated control of electromagnetic switching valve and motor speed.

[0014] 3. Fault self-diagnosis and protection mechanism: The intelligent controller integrates a multi-parameter monitoring system to achieve three-level protection. Level 1 warning: Monitor the rate of temperature change (ΔT / Δt > 10℃ / s) and provide a 5-second advance warning of potential faults; Level 2 protection: When motor stall is detected (current > 3 times the rated value for 0.5 seconds), the power supply is automatically cut off; Level 3 safety: When the cleaning fluid tank level is below 10%, it will be forcibly switched to gas mode and a replenishment reminder will be sent to the ECU via the CAN bus. It is TÜV certified that the system false alarm rate is <0.3% and the mean time between failures (MTBF) is >5000 hours.

[0015] 4. Optimized structure and low power consumption design, lightweight design: The pump body adopts a double-layer structure combining PPS+30% GF corrosion-resistant plastic and 316L stainless steel, reducing weight by 30% and achieving an impact strength of 120kJ / m², passing the ISO16750-3 vibration test (20g@2000Hz); low power consumption operation: standby power consumption <0.5W, average power consumption during operation <5W, only 1 / 3 of the traditional system; communicates with the vehicle ECU via CAN bus, supports OTA upgrade cleaning strategy, and is compatible with SAE L2-L5 level autonomous driving systems. Attached Figure Description

[0016] Figure 1 This is a cleaning process diagram of the present invention. Detailed Implementation

[0017] The present invention will be further described below with reference to the accompanying drawings: This embodiment of the intelligent cleaning method based on a brushless DC motor is characterized by an integrated design of the motor and pump body with a built-in heat dissipation channel; the heat dissipation channel is filled with a phase change material with a melting point of 50-65℃; and an intelligent controller is used to control the gas-liquid mixing cleaning module to switch the pump body cleaning mode.

[0018] The gas-liquid mixing cleaning module includes liquid jetting and gas purging sub-modules, and the mode switching is realized through electromagnetic switching valve. The cleaning parameters are dynamically adjusted according to the pollution detection data of the sensor. The dynamic adjustment adopts a fuzzy PID algorithm combined with an LSTM machine learning model. The LSTM model predicts future pollution trends based on historical pollution detection data.

[0019] The motor's drive circuit supports a wide voltage input of 12V / 24V, employs a sensorless FOC control algorithm, and combines an adaptive sliding mode observer to achieve stable operation across the entire speed range. The position estimation error of the adaptive sliding mode observer is less than 0.5°.

[0020] The intelligent controller integrates a fault diagnosis module to monitor the motor voltage, current, temperature and temperature change rate in real time. When the temperature change rate exceeds 10℃ / s, an early warning is triggered, and when it exceeds 15℃ / s, the power supply is cut off.

[0021] The pump body is equipped with a cleaning fluid tank, which has a built-in heater and an ultrasonic level sensor. It automatically heats the cleaning fluid in low-temperature environments and switches to gas-only cleaning when the fluid level is low. The heater has a power of 50-100W and a heating rate of 2℃ / min.

[0022] The pump body adopts a double-layer structure combining corrosion-resistant plastic and stainless steel. The corrosion-resistant plastic is PPS+30%GF, and the stainless steel is 316L. It communicates with the vehicle ECU via CAN bus, with an average power consumption of <5W and a standby power consumption of <0.5W.

[0023] See attached document Figure 1 In practical application, the specific cleaning steps of the method of the present invention are as follows: the entire system is started, the contamination detection sensor first performs contamination detection, and the result is fed back to the intelligent controller. When the contamination is greater than the threshold, the cleaning mode is selected according to the degree of contamination. After cleaning, the contamination detection is performed again. If the standard is met, the work stops and enters the standby state. If the standard is not met, the cleaning intensity is increased and the cleaning is performed again.

[0024] Motor selection: Maxon EC-i 40 brushless motor with rated power of 120W and speed range of 3000-12000rpm, conforming to AEC-Q100 Grade 0 standard.

[0025] Sensor configuration: Pollution detection: Laser scattering sensor (model: Sensirion SPS30, detection accuracy ±2%) + image sensor (model: Sony IMX490, resolution 1920×1080) Environmental monitoring: Temperature and humidity sensor (model: Bosch BME680, -40℃~+85℃, accuracy ±0.5℃), barometric pressure sensor (model: TE MS5837, accuracy ±0.1kPa). Cleaning fluid system: Uses environmentally friendly cleaning agent with a freezing point of -30℃, pipeline pressure resistance of 3MPa, built-in filter element (filtration accuracy of 5μm), and conforms to ISO 22241 diesel vehicle AdBlue standard.

[0026] The intelligent controller uses the Renesas RH850 / P1X-M microcontroller with a main frequency of 240MHz, supports ASIL-D level functional safety, and integrates 64KB ECC RAM. Example

[0027] 1. Heat dissipation performance test Test conditions: Ambient temperature 40℃, motor running continuously at full load Test equipment: FLIR A655sc infrared thermal imager Result comparison:

[0028] 2. Cleaning effect test Test subject: 1.2-megapixel camera, LiDAR (128-line cable) Pollution type: Mud splash (equivalent to SAE J400 standard Class III pollution)

[0029] 3. Reliability Testing Testing Standard: ISO 16750-4 Environmental Testing of Automotive Electronic Equipment Through the project: Temperature cycling (-40℃ to +85℃, 1000 cycles, heating rate 5℃ / min) Vibration test (10-2000Hz, 20g, 24 hours for each of the three axes) Salt spray test (5% NaCl, 96 hours, conforming to ASTM B117) This invention effectively improves sensor cleaning efficiency and system reliability by integrating a brushless DC motor, employing multi-mode intelligent cleaning, and a fault self-diagnosis mechanism, thereby reducing the system misjudgment rate caused by sensor surface contamination. 1. Core parameters of the main controller

[0030] 2. Core parameters of the motor

[0031] 3. Pollution detection sensors

[0032] 4. Current sensor

[0033] Model: Allegro ACS712 (ACS712ELCTR-05B-T), connected in series with the motor bus, detection range 0-5A (accuracy ±1.5%), real-time monitoring of motor current, power cut-off when stall current >15A (3 times rated value) for 0.5 seconds. 5. Water pump

[0034] 6. Gas-liquid mixing cleaning

[0035] Electromagnetic switching valve: SMC VQZ series (model: VQZ2220-5L1-C6), response time <10ms, working pressure 0.1-1.0MPa, achieving seamless switching between liquid (0.5-2MPa) and gaseous (0.8-1.5MPa) modes (50% faster response speed than mechanical valves).

[0036] Nozzle design: Liquid nozzle (0.8mm orifice, 30° spray angle) and gas nozzle (1.2mm orifice, 50m / s airflow velocity) are both made of 316L stainless steel and installed directly in front of the sensor lens (10cm away) to ensure thorough cleaning coverage. 7. Cleaning fluid system

[0037] Heater: PTC heater (model: ZYK-PTC-50), power adjustable from 50-100W, heating rate 2℃ / min, automatically heats the cleaning fluid (-30℃ freezing point environmentally friendly cleaning agent) at low temperatures (<-10℃) to prevent pipeline freezing.

[0038] Filter element: Sintered metal filter element (316L material, filtration accuracy 5μm), installed in the cleaning fluid inlet line, filters impurities to prevent nozzle clogging (compliant with ISO 22241 Diesel Vehicle AdBlue standard). Although the present invention has been illustrated and described with reference to preferred embodiments, those skilled in the art will understand that various changes in form and detail are possible within the scope of the claims.

Claims

1. A smart driving cleaning method based on a brushless DC motor, characterized in that: The motor and pump body are integrated into a design with a built-in heat dissipation channel. The heat dissipation channel is filled with a phase change material with a melting point of 50-65℃. The gas-liquid mixing cleaning module is controlled by an intelligent controller to switch the pump body cleaning mode.

2. The intelligent driving cleaning method based on a brushless DC motor according to claim 1, characterized in that: The gas-liquid mixing cleaning module includes liquid jetting and gas purging sub-modules, and the mode switching is realized through electromagnetic switching valve. The cleaning parameters are dynamically adjusted according to the pollution detection data of the sensor. The dynamic adjustment adopts a fuzzy PID algorithm combined with an LSTM machine learning model. The LSTM model predicts future pollution trends based on historical pollution detection data.

3. The intelligent driving cleaning method based on a brushless DC motor according to claim 1, characterized in that: The motor's drive circuit supports a wide voltage input of 12V / 24V, employs a sensorless FOC control algorithm, and combines an adaptive sliding mode observer to achieve stable operation across the entire speed range. The position estimation error of the adaptive sliding mode observer is less than 0.5°.

4. The intelligent driving cleaning method based on a brushless DC motor according to claim 1, characterized in that: The intelligent controller integrates a fault diagnosis module to monitor the motor voltage, current, temperature and temperature change rate in real time. When the temperature change rate exceeds 10℃ / s, an early warning is triggered, and when it exceeds 15℃ / s, the power supply is cut off.

5. The intelligent driving cleaning method based on a brushless DC motor according to claim 1, characterized in that: The pump body is equipped with a cleaning fluid tank, which has a built-in heater and an ultrasonic level sensor. It automatically heats the cleaning fluid in low-temperature environments and switches to gas-only cleaning when the fluid level is low. The heater has a power of 50-100W and a heating rate of 2℃ / min.

6. The intelligent driving cleaning method based on a brushless DC motor according to claim 1, characterized in that: The pump body adopts a double-layer structure combining corrosion-resistant plastic and stainless steel. The corrosion-resistant plastic is PPS+30%GF, and the stainless steel is 316L. It communicates with the vehicle ECU via CAN bus, with an average power consumption of <5W and a standby power consumption of <0.5W.

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