Automatic spreading device for snow-melting agent

Abstract

The invention relates to the technical field of road maintenance equipment, and discloses an automatic spreading device for a snow-melting agent, which realizes dynamic and accurate matching of the spreading amount of the snow-melting agent with the traffic flow speed, the rainfall type and the environment temperature by fusing multi-source environmental data and a self-adaptive control algorithm, and remarkably improves the spreading uniformity of a high-risk road section. Accumulated snow trend prediction and preventive spreading functions are integrated, so that the response capability to sudden ice and snow weather is enhanced; by combining solar energy and commercial power complementary power supply and an abnormal state emergency control mechanism, continuous and reliable operation in an extreme environment is ensured; the remote interaction and real-time monitoring function of the mobile terminal further reduces the manual intervention requirement; the device has the advantages of being intelligent, low in energy consumption and high in adaptability, and a safe and efficient snow melting solution is provided for high-risk road sections.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of road maintenance equipment, in particular to an automatic snow-melting agent spreading device. BACKGROUND

[0002] Road snow melting refers to melting snow on the road by using various methods and technologies to ensure smooth traffic on the road, generally using snow-melting agent spreading on the road to achieve snow melting effect.

[0003] At present, road snow melting operation mainly adopts vehicle-mounted spreading device or manual spreading method. The vehicle-mounted device relies on the driver to manually adjust the snow-melting agent flow according to experience, which is difficult to respond to the change of traffic speed and the fluctuation of snowfall intensity in real time, and is easy to cause overloading or insufficient spreading; manual spreading is low in efficiency and poor in uniformity, especially in night or bad weather, which has safety hazards.

[0004] In high-risk sections such as sharp bends and steep slopes, the limitations of the prior art are further highlighted. The terrain of such sections is complex, and the traffic speed difference is significant. If there is snow, it is easy to cause risks by slipping, and the traditional manual spreading or vehicle-mounted spreading device is difficult to spread snow-melting agent on high-risk sections in time, which aggravates the risk of traffic accidents, and manual or vehicle-mounted spreading of snow-melting agent is also more cumbersome, time-consuming and laborious. Therefore, an automatic snow-melting agent spreading device is proposed. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides an automatic snow-melting agent spreading device to solve the problems in the background art.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical scheme: an automatic snow-melting agent spreading device, comprising:

[0007] a support fixedly installed on the foundation or guardrail of a sharp bend or steep slope section for bearing the overall structure;

[0008] a material box installed on the support for storing snow-melting agent, the upper end of the material box being provided with a box cover, and the discharge port of the material box being provided with an infrared opposite-acting sensor for detecting the remaining amount;

[0009] a spreading control unit, comprising:

[0010] a motor fixed to the support;

[0011] b) a spreading turntable installed on the output end of the motor for spreading snow-melting agent by centrifugal force;

[0012] c) a material guide cover arranged on the periphery of the spreading turntable for guiding the diffusion direction of the snow-melting agent;

[0013] d) an electric control valve installed on the discharge port of the material box for adjusting the flow of snow-melting agent;

[0014] The controller is mounted on the material box and integrates a 5G communication unit. The controller wirelessly interacts with traffic monitoring system data, meteorological monitoring stations, and mobile terminals through the 5G communication unit to obtain real-time traffic speed, road section precipitation type data (including snowfall and rainfall), and ambient temperature. Based on the road section traffic speed, precipitation type data, and ambient temperature, the controller generates a control signal, which drives the opening of the electronically controlled valve outlet and the speed of the motor through an electrical signal connection, thereby achieving dynamic matching of the snow melting agent spreading amount with the traffic speed and snowfall conditions on the road section.

[0015] Solar power supply system, including:

[0016] a) Solar panels, installed on the surface of the box cover;

[0017] b) A power supply battery, fixed on the bracket, supports charging via a mains charging interface, and is electrically connected to the solar panel to power the electronically controlled valve, motor, infrared sensor and controller.

[0018] Preferably, the controller generates the control signal according to the following composite conditions:

[0019] When snowfall is detected, the spreading rate baseline value is calculated based on the product relationship between traffic speed and snowfall amount;

[0020] When rainfall is detected and the ambient temperature is ≤0°C, the icing risk spreading amount is calculated according to the equivalent snowfall model;

[0021] When there is no precipitation but the ambient temperature is ≤-5℃, start the preventive spreading mode;

[0022] The opening of the discharge port of the electric-controlled valve and the speed of the motor are driven by an electrical signal connection to achieve dynamic matching of the snow-melting agent spreading amount with the traffic speed, precipitation type and ambient temperature.

[0023] Preferably, the controller has a built-in adaptive control algorithm, specifically including:

[0024] Benchmark value calculation rules:

[0025] When snowfall is detected, the reference value of spreading amount Q1 = k1 × v × s, where v is the traffic speed (km / h), s is the snowfall (mm / h), and k1 is the snow amount correction coefficient (0.8≤k1≤1.5);

[0026] When rainfall is detected and the ambient temperature is ≤0°C, the spreading amount reference value Q2=k2×v×r×T ice , where r is rainfall (mm / h), T ice is the temperature influence factor (T ice =1-0.1×|temperature|), k2 is the freezing rain compensation coefficient;

[0027] When there is no precipitation but the ambient temperature is ≤-5℃, the reference value of the spreading amount Q3=k3x|temperature| 2 , k3 is the low temperature gradient coefficient.

[0028] Preferably, the reference value in the adaptive control algorithm satisfies the following dynamic priority arbitration:

[0029] If multiple composite conditions are met at the same time, the highest spreading amount is executed according to the priority of Q1>Q2>Q3;

[0030] When Q1 and Q2 coexist, take the maximum value of Q1 and Q2 and add a 20% redundancy.

[0031] Preferably, the adaptive control algorithm uses an actuator coupled control electric valve and motor, specifically including:

[0032] Electric valve 8 opening proportional coefficient C valve =Q x / Q max , wherein Q x represents the reference value of the spreading amount; Q max is the maximum flow of the hopper; and C valve ≥5% is forced to open the spreader;

[0033] Motor 6 speed N motor =N base x(1+0.05xv), wherein N base is the reference speed, and is limited by the critical speed N critical of the spreading disc 7.

[0034] Preferably, the controller is built-in with a predictive control module, which predicts the future 30-minute road snow trend through a machine learning model, and dynamically adjusts the electric valve opening and motor speed;

[0035] The input parameters of the machine learning model include real-time traffic speed, ambient temperature, snow / rain probability and historical spreading amount data, and the output is the recommended spreading amount;

[0036] When the snow accumulation risk is predicted, the controller 10 starts the spreading 5-10 minutes in advance, and the spreading amount is not less than 80% of the real-time calculation value.

[0037] Preferably, the mobile terminal is a smart phone or a municipal maintenance management terminal, and its interactive interface includes:

[0038] Spreading start / stop button;

[0039] Snow thickness parameter input slider (range 0-20cm);

[0040] Real-time spreading state display area (including spreading amount, motor speed, and electric control valve opening);

[0041] Fault alarm pop-up window (trigger conditions include material tank remaining amount < 10%, power supply battery voltage anomaly, and communication interruption);

[0042] The mobile terminal interacts with the controller through the 5G communication unit, supports remote firmware upgrade and historical data export.

[0043] Preferably, the solar power supply system is provided with an intelligent switching circuit, and the following energy management strategies are executed:

[0044] When the power supply battery power > 80% and the light intensity received by the solar panel > 500W / m 2 , the solar panel directly supplies power to the load, and the mains power charging is turned off;

[0045] When the power supply battery power < 20% and the continuous overcast day is more than 48 hours, the mains power charging is automatically activated, and the maximum power of the motor is limited to 70% of the rated value;

[0046] When the temperature < -20℃, the mains power is used to maintain the temperature of the power supply battery.

[0047] The present application realizes the dynamic and accurate matching of the snow-melting agent spreading amount, the vehicle flow speed, the precipitation type and the environmental temperature by fusing multi-source environmental data and adaptive control algorithm, significantly improves the spreading uniformity of high-risk road sections, integrates the accumulated snow trend prediction and preventive spreading function, enhances the response capability to sudden ice and snow weather, combines the solar and mains power complementary power supply and abnormal state emergency control mechanism, ensures the continuous and reliable operation in extreme environment, and further reduces the manual intervention demand through the mobile terminal remote interaction and real-time monitoring function. The device has the characteristics of intelligence, low energy consumption and high adaptability, provides a safe and efficient snow-melting solution for high-risk road sections.

[0048] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and attained by the structure particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0049] Fig. 1 It is a schematic diagram of the overall structure of the present application;

[0050] Fig. 2 It is a schematic diagram of the separation structure of the box cover and the material tank of the present application;

[0051] Fig. 3 It is a schematic diagram of the control system frame of the snow-melting agent automatic spreading device of the present application.

[0052] In the figure: 1, support; 2, material box; 3, box cover; 4, power supply battery; 5, solar panel; 6, motor; 7, spreading turntable; 8, electric control valve; 9, material guide cover; 10, controller; 11, infrared opposite transmission sensor. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0054] Please refer to Figs. 1-3 The snow-melting agent automatic spreading device in the present application realizes precise, efficient and low-energy-consumption ice and snow removal operation by collecting vehicle speed, snow thickness, environmental temperature and humidity and weather data in real time, combining adaptive control algorithm and prediction model and dynamically adjusting snow-melting agent spreading amount.

[0055] I. Overall structure

[0056] The device is composed of the following core components, and each component cooperates to realize intelligent spreading function:

[0057] 1. Support 1

[0058] Material and installation: the support 1 adopts a Q355B carbon steel welded frame, the surface is hot-dip galvanized, the wind load resistance grade is greater than or equal to 10, and the support 1 is fixed on the foundation or wave beam guardrail of sharp bend and steep slope road section through pre-buried bolts, and the bearing capacity is greater than or equal to 500 kg.

[0059] 2. Material box 2

[0060] Capacity and material: the material box 2 is a rectangular stainless steel container with a volume of 200 liters, the inner wall is coated with a polytetrafluoroethylene (PTFE) corrosion-resistant coating to prevent corrosion of the snow-melting agent. A closable box cover 3 is provided on the top of the material box, and a silicone seal strip is used on the edge to prevent the snow-melting agent from absorbing moisture and caking. An infrared opposite transmission sensor 11 is installed at the discharge port, which is composed of a transmitting end and a receiving end. The installation method is to symmetrically install the transmitting end and the receiving end at a 10% excess height position on the side wall of the material box 2. The trigger logic is: when the snow-melting agent blocks the infrared light beam, it is determined that there is excess amount, and the light beam transmission alarms.

[0061] Discharge port design: the bottom of the material box 2 is a conical structure, the discharge port diameter is 100 mm, and the inside is welded with spiral guide vanes to ensure that the snow-melting agent flows uniformly into the spreading unit under the action of gravity, avoiding blockage.

[0062] 3. Spreading control unit

[0063] Motor 6

[0064] Selection and parameters: adopt brushless DC motor (BLDC), rated power 500W, peak torque 5N·m, speed range 0-3000r / min. The motor 6 is vertically installed inside the bracket below through the flange plate.

[0065] Control mode: the speed of the motor 6 is adjusted by the PWM signal (duty ratio 0-100%) output by the controller 10 below, with a speed accuracy error of ±1%.

[0066] Spreading turntable 7

[0067] Structural design: the turntable is an aluminum alloy disc with a diameter of 300mm, and the surface is evenly distributed with multiple arc-shaped blades.

[0068] Working principle: when the motor 6 drives the spreading turntable 7 to rotate at high speed, the snow-melting agent is thrown out by centrifugal force, and the arc-shaped blades further scatter the particles, ensuring that the spreading coverage width reaches 3-5 meters.

[0069] Material guide cover 9

[0070] Material and shape: the material guide cover 9 is made of 304 stainless steel and has a semicircular arc shape, with both ends extended outward to guide the snow-melting agent and make it spread out in a fan shape (radius 350mm).

[0071] Electric control valve 8

[0072] Structure and accuracy: the electric control valve 8 adopts a butterfly valve structure driven by a stepping motor, with a continuous adjustable opening degree from 0% (fully closed) to 100% (fully open), a flow control accuracy of ±2%, and a control opening angle by the controller 10 below.

[0073] 4. Controller 10

[0074] Hardware configuration

[0075] Main control chip: STM32H743VIT6 (ARM Cortex-M7 core, 400MHz frequency), with built-in floating point operation unit (FPU) and support for real-time calculation of complex algorithms.

[0076] Communication and perception:

[0077] 5G module: supports Sub-6GHz frequency band, with uplink speed of 1Gbps and downlink speed of 2Gbps, used for wireless interaction with traffic monitoring system data, weather monitoring station and mobile terminal;

[0078] Receive the excess signal of the infrared opposite sensor 11.

[0079] Software functions:

[0080] Real-time operating system (RTOS): FreeRTOS is used to implement multi-task scheduling, ensuring the parallel processing of data acquisition, algorithm operation, and control instructions.

[0081] Control algorithm library: built-in adaptive control algorithm and predictive control module.

[0082] 5. Solar power system

[0083] Photovoltaic module: monocrystalline silicon solar panel 5 (conversion efficiency 22%), size 600mm x 400mm, installed on the surface of the box cover 3;

[0084] Energy storage unit: power supply battery 4 uses 48V / 20Ah lithium iron phosphate battery pack, cycle life >2000 times, supports vehicle interface charging, and its external is protected by a metal shell, installed on the bracket 1.

[0085] Energy management:

[0086] Charge and discharge controller: MPPT (maximum power point tracking) algorithm is used to optimize the output efficiency of the solar panel 5 in real time.

[0087] Intelligent switching circuit: implements energy management strategy.

[0088] II. Workflow

[0089] 1. System initialization and hardware self-test

[0090] Solar power start:

[0091] Light intensity detection: solar panel 5 detects the current light intensity as 600W / m 2 , power supply battery 4 power 85%, triggers the intelligent switching circuit to turn off the mains charging, directly powers the load;

[0092] After the controller 10 is powered on, the self-test program is started:

[0093] Detect the winding resistance of the motor 6 (normal value 3.5Ω), the full open / full close action of the electric control valve 8 (time consumption 0.4 seconds);

[0094] Verify the infrared opposite sensor 11 signal.

[0095] 2. Data acquisition and communication connection

[0096] Real-time data acquisition:

[0097] Traffic data: current road traffic speed v is obtained from the traffic monitoring system through the 5G communication unit;

[0098] Weather data: the weather monitoring station provides precipitation type as snowfall, snowfall amount s, and environment temperature T;

[0099] Local sensor: Infrared reflection sensor 11 monitors the remaining amount of the material box continuously;

[0100] Mobile terminal connection: The municipal maintenance terminal synchronizes the snow thickness parameter (initial value 0 cm) with the controller 10 in real time through an encrypted 5G channel.

[0101] 3. Control signal generation

[0102] 3.1 The controller 10 generates a control signal according to the following composite conditions:

[0103] When snowfall is detected, the spreading amount reference value is calculated based on the product relationship between traffic speed and snowfall amount;

[0104] When rain is detected and the ambient temperature is ≤0℃, calculate the ice risk spreading amount according to the equivalent snowfall amount model;

[0105] When there is no precipitation but the ambient temperature is ≤-5℃, start the preventive spreading mode;

[0106] Through the connection of the electric signal, the opening degree of the electric control valve 8 and the rotating speed of the motor 6 are driven, so as to realize the dynamic matching of the snow-melting agent spreading amount, traffic speed, precipitation type and ambient temperature;

[0107] 3.2 The reference value calculation rule of the adaptive control algorithm:

[0108] When snowfall is detected, the spreading amount reference value Q1 = k1 × v × s, where v is the traffic speed (km / h), s is the snowfall amount (mm / h), and k1 is the snow amount correction coefficient (0.8 ≤ k1 ≤ 1.5);

[0109] When rain is detected and the ambient temperature is ≤0℃, the spreading amount reference value Q2 = k2 × v × r × T ice , where r is the rainfall amount (mm / h), T ice is the temperature influence factor (T ice = 1-0.1×|temperature|), and k2 is the freezing rain compensation coefficient;

[0110] When there is no precipitation but the ambient temperature is ≤-5℃, the spreading amount reference value Q3 = k3 × |temperature| 2 , and k3 is the low temperature gradient coefficient.

[0111] 3.3 The reference value meets the following dynamic priority arbitration:

[0112] If multiple composite conditions are met at the same time, the highest spreading amount is executed according to the priority of Q1 > Q2 > Q3;

[0113] When Q1 and Q2 coexist, take the maximum value of Q1 and Q2 and add a 20% redundancy.

[0114] 4. Actuator dynamic adjustment

[0115] The adaptive control algorithm employs actuator-coupled control of the electrically controlled valve 8 and the motor 6, specifically including:

[0116] Proportional coefficient C of the opening degree of the electrically controlled valve 8 valve = Q x / Q max , wherein Q x represents the reference value of the spreading amount; Q max is the maximum flow rate of the material tank; and C valve ≥ 5% is forcibly opened for spreading;

[0117] Motor 6 rotation speed N motor = N base × (1+0.05×v), wherein N base is the reference rotation speed, and is limited by the critical rotation speed N critical of the spreading turntable (7).

[0118] 5. Prediction control module intervention

[0119] Predict the future 30-minute road surface snow trend through a machine learning model, and dynamically adjust the opening degree of the electrically controlled valve 8 and the rotation speed of the motor 6;

[0120] The input parameters of the machine learning model include real-time traffic speed, environmental temperature, snow / rain probability, and historical spreading amount data, and the output is the recommended spreading amount;

[0121] When the risk of snow accumulation is predicted, the controller 10 starts spreading 5-10 minutes in advance, and the spreading amount is not less than 80% of the real-time calculation value.

[0122] 6. Mobile terminal interaction and alarm

[0123] Operation interface functions:

[0124] Spreading start / stop button;

[0125] Snow thickness parameter input slider (range 0-20 cm);

[0126] Real-time spreading state display area (including spreading amount, motor 6 rotation speed, electrically controlled valve 8 opening degree);

[0127] Fault alarm pop-up window (triggering conditions include material tank 2 remaining amount <10%, power supply battery 4 voltage anomaly, communication interruption);

[0128] The mobile terminal interacts with the controller 10 through a 5G communication unit, supports remote firmware upgrade and historical data export.

[0129] 7. Energy management strategy

[0130] When the power supply battery 4 power > 80%, and the solar panel 5 received light intensity > 500W / m 2 When the power supply battery 4 power > 80%, and the solar panel 5 received light intensity > 500W / m

[0131] When the power supply battery 4 power < 20%, and the continuous overcast day more than 48 hours, automatically activate the mains charging, and limit the motor 6 maximum power to 70% of the rated value;

[0132] When the temperature < -20℃, prefer to use the mains to maintain the power supply battery 4 temperature.

[0133] Three, typical application scenarios

[0134] The following scenarios show the device's multi-working condition adaptability through different input parameters:

[0135] Scenario 1: snow + medium speed traffic

[0136] The controller 10 obtains parameters through traffic monitoring system data, meteorological monitoring station:

[0137] Precipitation type: snow, snowfall s = 4mm / h;

[0138] Traffic speed v = 50km / h, ambient temperature T = -5℃;

[0139] Control logic:

[0140] Reference value calculation:

[0141] Q1 == 1.3x50x4 = 260kg / h

[0142] Prediction correction: model predicts that the snowfall in the next 30 minutes increases to 6mm / h, and the recommended spreading amount increases to 312kg / h.

[0143] Execution response:

[0144] Electric control valve opening 62.4%(312 / 500), motor speed 1000x(1+0.05x50)=3500rpm;

[0145] Spreading coverage width 5.2 meters, residual rate of deicing agent < 3%, preventive spreading response time 8 minutes.

[0146] Scenario 2: freezing rain + low temperature

[0147] Parameters:

[0148] Precipitation type: rain, rainfall r = 6mm / h;

[0149] Ambient temperature T = -2℃, traffic speed v = 30km / h;

[0150] Control logic:

[0151] Equivalent snowfall calculation:

[0152] T ice = 1 - 0.1 x 2 = 0.8

[0153] Q2 = 0.85 x 30 x 6 x 0.8 = 122.4 kg / h

[0154] Execution response: electric control valve opening 24.5%, motor speed 1000 x (1 + 0.05 x 30) = 2500 rpm;

[0155] Snow melting agent effectively inhibits freezing rain icing, road friction coefficient from 0.15 to 0.38.

[0156] Scenario 3: Extremely low temperature without precipitation

[0157] Parameters:

[0158] No precipitation, ambient temperature T = -18℃, vehicle speed v = 10 km / h;

[0159] Control logic:

[0160] Reference value calculation:

[0161] Q3 = 0.06 x 18 2 = 19.44 kg / h

[0162] Forced distribution: valve opening 3.9% (<5% threshold), forced to open to 5%, distribution amount 25 kg / h;

[0163] Preventive distribution inhibits black ice formation, continuous operation for 12 hours without icing report.

[0164] Scenario 4: Fault alarm

[0165] Parameters:

[0166] 5G communication interruption for 60 seconds or infrared beam sensor 11 detects insufficient material box 2 or abnormal voltage of power supply battery 4;

[0167] Control response:

[0168] Trigger alarm pop-up window "communication interruption" or "insufficient amount of snow melting agent" or "abnormal voltage".

[0169] Scenario 5: Intelligent switching circuit

[0170] Scenario 1 (sufficient light):

[0171] Solar panel directly supplies load, city power is off, battery power is stable at 90%.

[0172] Scenario 2 (continuous overcast) :

[0173] Overcast 50 hours, battery power 18%, activate mains charging and limit motor power to 70% (4000 rpm → 2800 rpm).

[0174] Scenario 3 (extreme low temperature) :

[0175] Temperature -25℃, priority mains heating battery to -10℃, maintain controller running.

[0176] Four, summary

[0177] The embodiment provides a snow-melting agent automatic spreading device, which is fixedly installed on the side of a road through a support, integrates a material box, a spreading control unit and a solar power supply system, and realizes non-vehicle precise spreading. The controller dynamically adjusts the opening degree of an electric control valve and the rotating speed of a motor based on real-time vehicle flow speed, precipitation type and environmental temperature through a self-adaptive algorithm, and optimizes a spreading strategy by means of a machine learning model to predict a snow accumulation trend; a mobile terminal supports remote parameter setting and state monitoring, and combines a fault alarm mechanism to ensure operation reliability; 5G communication is used to receive meteorological and traffic data, and intelligent switching between solar power and mains power is used to ensure continuous operation in an extreme environment, and the device is suitable for intelligent snow-melting management of high-risk road sections such as sharp bends and steep slopes.

Claims

1. An automatic snow-melting agent spreading device, characterized in that: include: The bracket (1) is fixedly installed on the foundation or guardrail of a sharp bend or steep slope section of the road to support the entire structure; A material box (2) is mounted on the bracket (1) and is used to store snow-melting agent. A box cover (3) is mounted on the upper end of the material box (2). An infrared radiation sensor (11) for detecting the remaining amount is mounted on the discharge port of the material box (2); Spreading control unit, including: a) a motor (6), fixed on the bracket (1); b) a spreading turntable (7), mounted on the output end of the motor (6), for spreading the snow-melting agent by centrifugal force; c) a material guide cover (9), which is arranged on the periphery of the spreading turntable (7) and is used to guide the diffusion direction of the snow-melting agent; d) an electrically controlled valve (8), installed at the outlet of the material box (2), for regulating the flow of the snow-melting agent; The controller (10) is installed on the material box (2) and is integrated with a 5G communication unit. The controller wirelessly interacts with traffic monitoring system data, a weather monitoring station, and a mobile terminal through the 5G communication unit to obtain real-time traffic speed, road section precipitation type data (including snowfall and rainfall), and ambient temperature; based on the road section traffic speed, precipitation type data, and ambient temperature, a control signal is generated, and the opening of the discharge port of the electric control valve (8) and the speed of the motor (6) are driven through an electrical signal connection to achieve dynamic matching of the amount of snow melting agent spread with the traffic speed and the amount of snow on the road section; and a signal sent by an infrared radiation sensor (11) is received; Solar power supply system, including: a) a solar panel (5), mounted on the surface of the box cover (3); b) A power supply battery (4), fixed on the bracket (1), supports charging via a mains charging interface, and is electrically connected to the solar panel (5) to supply power to the electric control valve (8), the motor (6), the infrared radiation sensor (11) and the controller (10).

2. The automatic snow-melting agent spreading device according to claim 1, characterized in that: The controller (10) generates a control signal according to the following composite conditions: When snowfall is detected, the spreading rate baseline value is calculated based on the product relationship between traffic speed and snowfall amount; When rainfall is detected and the ambient temperature is ≤0°C, the icing risk spreading amount is calculated according to the equivalent snowfall model; When there is no precipitation but the ambient temperature is ≤-5℃, start the preventive spreading mode; The opening of the discharge port of the electric control valve (8) and the rotation speed of the motor (6) are driven by an electrical signal connection, thereby achieving dynamic matching of the snow-melting agent spreading amount with the traffic speed, precipitation type and ambient temperature.

3. The automatic snow-melting agent spreading device according to claim 1, characterized in that: The controller (10) has a built-in adaptive control algorithm, specifically including: Benchmark value calculation rules: When snowfall is detected, the reference value of spreading amount Q1 = k1 × v × s, where v is the traffic speed (km / h), s is the snowfall (mm / h), and k1 is the snow amount correction coefficient (0.8≤k1≤1.5); When rainfall is detected and the ambient temperature is ≤0°C, the spreading amount reference value Q2=k2×v×r×T ice , where r is rainfall (mm / h), T ice is the temperature influence factor (T ice =1-0.1×|temperature|), k2 is the freezing rain compensation coefficient; When there is no precipitation but the ambient temperature is ≤-5℃, the reference value of the spreading amount Q3=k3×|temperature| 2 , k3 is the low temperature gradient coefficient.

4. The automatic snow-melting agent spreading device according to claim 1, characterized in that: The reference value in the adaptive control algorithm satisfies the following dynamic priority arbitration: If multiple compound conditions are met at the same time, the highest spreading amount will be executed according to the priority of Q1>Q2>Q3; When Q1 and Q2 coexist, the maximum value of Q1 and Q2 is taken and a 20% redundancy is added.

5. The automatic snow melting agent spreading device according to claim 1, characterized in that: The adaptive control algorithm uses actuator coupling to control the electronically controlled valve (8) and the motor (6), specifically including: Opening proportional coefficient C of the electric control valve (8) valve =Q x / Q max , where Q x Indicates the base value of spreading amount; Q max is the maximum flow rate of the material box; and C valve When the percentage is ≥5%, the spreading is forced to start; Motor (6) speed N motor =N base ×(1+0.05×v), where N base is the reference speed and is limited by the critical speed N of the spreading disc (7) critical .

6. The automatic snow-melting agent spreading device according to claim 1, characterized in that: The controller (10) has a built-in prediction control module, which predicts the road snow accumulation trend in the next 30 minutes through a machine learning model and dynamically adjusts the opening of the electronically controlled valve (8) and the speed of the motor (6); The input parameters of the machine learning model include real-time traffic speed, ambient temperature, snow / rainfall probability and historical spreading rate data, and the output is a recommended spreading rate; When the risk of snow accumulation is predicted, the controller (10) starts spreading 5-10 minutes in advance, and the spreading amount is not less than 80% of the real-time calculated value.

7. The automatic snow-melting agent spreading device according to claim 1, characterized in that: The mobile terminal is a smart phone or a municipal maintenance management terminal, and its interactive interface includes: Spreading start / stop button; Snow thickness parameter input slider (range 0-20cm); Real-time spreading status display area (including spreading amount, motor (6) speed, and electric control valve (8) opening); Fault alarm pop-up window (trigger conditions include the remaining amount of the material box (2) is less than 10%, the power supply battery (4) voltage is abnormal, and communication is interrupted); The mobile terminal interacts with the controller (10) in an encrypted manner via a 5G communication unit, and supports remote firmware upgrades and historical data export.

8. The automatic snow-melting agent spreading device according to claim 1, characterized in that: The solar power supply system is equipped with an intelligent switching circuit to implement the following energy management strategies: When the power of the power supply battery (4) is greater than 80%, and the light intensity received by the solar panel (5) is greater than 500W / m 2 When the solar panel (5) directly supplies power to the load, the mains charging is turned off; When the power of the power supply battery (4) is less than 20% and it is cloudy for more than 48 hours, the mains charging is automatically activated and the maximum power of the motor (6) is limited to 70% of the rated value; When the temperature is less than -20°C, the mains power is used first to maintain the temperature of the power supply battery (4).

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