New energy automobile electric power intelligent monitoring system based on Internet of Things

Abstract

The invention belongs to the technical field of new energy automobile power monitoring, and discloses a new energy automobile power intelligent monitoring system based on the Internet of Things, a battery monitoring module monitors the state of a battery and sends the remaining capacity Qc and the capacity Qn of the battery to a central control module, and the central control module sends the remaining capacity Qc and the capacity Qn of the battery to an energy recovery decision module. By means of the mode, real-time monitoring of the battery is achieved, the energy recovery degree can be formulated according to the battery remaining capacity Qc of the battery, the travel prediction module is additionally arranged to conduct prediction calculation on the vehicle travelled distance # imgabs0 # according to the vehicle battery remaining capacity Qc, and the energy recovery degree can be formulated according to the vehicle battery remaining capacity Qc. Compared with the vehicle driving mileage S automatically predicted in the central control module, the accuracy of prediction of the vehicle driving mileage # imgabs1 # is improved, and the charging station screening module can select the optimal vehicle driving route according to the predicted vehicle driving mileage # imgabs2 #.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicle power monitoring, and in particular to a new energy vehicle power intelligent monitoring system based on the Internet of Things. Background Art

[0002] The power supply system of electric vehicles covers multiple elements such as battery packs, management systems, safety protection equipment, and communication lines. In addition to the core parts, the system also includes peripheral components such as charging protection modules, touch screens, and store power supplies. The battery pack, also known as the battery pack, is the core component of the power supply system. The number of battery packs varies depending on the design of the vehicle. There may be only one, or it may be composed of several or even dozens of battery packs.

[0003] For example, Chinese patent CN115566733A discloses a new energy intelligent management system integrating software and hardware, which includes: a user interface module for interaction between the client and the server; a new energy intelligent management module integrating software and hardware for visual real-time monitoring of power load, renewable energy power generation and electric vehicle status; a data exchange and communication module for providing decision instructions for charging and discharging of electric vehicles and maintaining data connection between electric vehicles and virtual power plant centers using wireless communication technology; a multi-model decision module, including two prediction models and one decision model, providing intelligent decision instructions for electric vehicles.

[0004] However, this technology has the following problems: it is not possible to calculate and predict the distance that an electric vehicle can travel by monitoring the power of the electric vehicle, and it is not possible to plan a suitable route for the electric vehicle based on the remaining power of the electric vehicle.

[0005] Based on this, the present invention designs a new energy vehicle power intelligent monitoring system based on the Internet of Things to solve the above problems. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a new energy vehicle power intelligent monitoring system based on the Internet of Things.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] An intelligent monitoring system for electric power of new energy vehicles based on the Internet of Things includes a central control module and the following components;

[0009] Battery monitoring module, used to collect battery current, voltage, temperature, and remaining power and battery capacity Qn and upload them to the central control module, which then calculates the remaining power The vehicle mileage S is automatically predicted based on the energy consumption per unit mileage E;

[0010] Energy recovery decision module, which is used to recover the excess kinetic energy released by the vehicle during braking or coasting, and convert the kinetic energy into electrical energy and store it in the battery;

[0011] The trip prediction module is used to receive the remaining battery power Data information and calculate the predicted vehicle mileage , and the vehicle mileage Send to the route planning module;

[0012] Route planning module, receiving And plan the driving route, and send the driving route to the charging station screening module;

[0013] A charging station screening module receives a driving route and screens out charging stations that match the battery model of the vehicle in the driving route;

[0014] A touch screen, which is fixedly mounted on the upper end of the vehicle center console and is used by the user to manually input the destination B;

[0015] The charging station management system is connected to the central control module through the communication module, and the central control module transmits the data information of the driving route to the charging station management system through the communication module;

[0016] The central control module is electrically connected to the battery monitoring module, the energy recovery decision module, the touch screen, and the communication module. The communication module is wirelessly connected to the charging station management system, and the charging station management system is wirelessly connected to the charging station.

[0017] Furthermore, the battery monitoring module includes a battery, a current sensor, a voltage sensor and a temperature sensor, the current sensor and the voltage sensor are electrically connected to the battery, the temperature sensor is fixedly installed on the battery, the current sensor, the voltage sensor, and the temperature sensor are electrically connected to the battery, the battery is connected to the energy recovery decision module, and the battery is electrically connected to the central control module.

[0018] Furthermore, the energy recovery decision module includes a pedal opening sensor, a motor controller, an inverter, a motor and a power converter. The pedal opening sensor is electrically connected to the motor controller, the motor controller is electrically connected to the inverter, the inverter is electrically connected to the motor, the motor is electrically connected to the power converter and the battery, and the pedal opening sensor and the motor controller are electrically connected to the central control module.

[0019] Furthermore, the energy recovery decision module also includes a decision unit, which receives the remaining power collected by the central control module. Set the energy recovery value ;

[0020]

[0021] Determine whether the decision unit performs energy recovery based on the SOC value:

[0022] When SOC>0.8, the decision-making unit does not perform energy recovery;

[0023] When 0.7≤SOC≤0.8, the decision unit performs energy recovery, and the current of energy recovery is less than the maximum charging current allowed by the battery;

[0024] When SOC<0.7, the decision unit performs energy recovery, and the energy recovery current is not affected by the maximum charging current allowed by the battery.

[0025] Furthermore, the trip prediction module includes a GPS locator, a high-definition camera and a vehicle speed sensor. The GPS locator and the high-definition camera are fixedly installed inside the vehicle, and the vehicle speed sensor is fixedly installed at the wheel; the GPS locator, the high-definition camera and the vehicle speed sensor are all electrically connected to the central control module.

[0026] Furthermore, the travel prediction module also includes a mileage prediction unit, which is used to receive data information from a GPS locator, a high-definition camera, and a vehicle speed sensor.

[0027] Furthermore, the mileage prediction unit predicts the vehicle mileage in the following steps;

[0028] Step 1: The calculation formula for the energy consumption per unit mileage of the vehicle is:

[0029]

[0030] E is the energy consumption per unit mileage, kW·h / km; P is the power demand during driving, kW; is the driving distance, km; t is the driving time, h;

[0031] Step 2: Power requirements during driving at a constant speed for:

[0032]

[0033] is the power demand, v is the uniform vehicle speed, km / h; C is the drag coefficient; A is the vehicle's frontal area, ; is the slope; f is the rolling resistance coefficient, N / kN; For electric drive efficiency; is the weight of the vehicle, kg; is the acceleration due to gravity;

[0034] Will Substituting into E, the energy consumption per unit mileage when the vehicle is traveling at a constant speed is :

[0035]

[0036] Step 3: Vehicle acceleration and power requirements during driving for:

[0037]

[0038] For power demand; is vehicle speed, km / h; is the vehicle rotation mass conversion factor; is the acceleration;

[0039] Will Substituted into E, the energy consumption per unit mileage when the vehicle accelerates for:

[0040]

[0041] In the formula, is the acceleration starting speed, km / h; is the acceleration end speed, km / h;

[0042] Step 4: The mileage energy consumption of the vehicle in the combination of constant speed driving and accelerated driving is , unit: kW.h;

[0043] Step 5: During braking, the energy recovered by the battery is :

[0044]

[0045] N is the number of braking times, is the braking time;

[0046] Step 6: Assume that the battery energy before departure is , and the remaining total energy of the vehicle battery is obtained for:

[0047] The driving range can be obtained from this , unit km;

[0048]

[0049] Furthermore, the mileage prediction unit calculates Compare with the mileage S predicted by the system:

[0050] like When , as the estimated mileage of the vehicle ;

[0051] like When , as the estimated mileage of the vehicle ;

[0052] like When , take S as the estimated mileage of the vehicle ;

[0053] Furthermore, the route planning module receives the remaining mileage of the vehicle predicted by the mileage prediction unit. , the route planning module plans a route to destination B;

[0054] The planning steps are as follows:

[0055] Step 1: The user inputs the destination B on the touch screen, and the touch screen uploads the destination to the central control module, which first plans multiple routes from the departure point A to the destination B;

[0056] Step 2: The central control module receives the vehicle mileage predicted by the mileage prediction unit , and determine whether the vehicle can reach destination B;

[0057] Step 3: The central control module determines the shortest route from the vehicle's departure point A to the destination B. Vehicle mileage the relationship between;

[0058] like , the central control module selects the route Push it to users as the optimal route;

[0059] like , the central control module sends all the planned routes to the charging station screening module, and the charging station screening module performs screening and judgment of the charging stations.

[0060] Furthermore, the steps of the charging station screening module to screen the charging station route information are as follows:

[0061] Step 1: The charging station management system uploads the location information and data information of the charging stations within the battery monitoring module kilometers of destination B to the charging station screening module;

[0062] Step 2: If there is a charging station within kilometers of destination B and the charging station within kilometers of destination B matches the vehicle charging current, the charging station screening module directly screens out the route Push it to users as the optimal route;

[0063] Step 3: If there is no charging station within kilometers of destination B, or the charging station within kilometers of destination B does not match the vehicle battery model, the charging station screening module will perform route screening;

[0064] Step 4: The charging station screening module selects the routes containing charging stations from the routes planned by the route planning module. The charging station screening module selects the charging stations that match the vehicle battery model from the routes containing charging stations. Finally, the shortest route containing the charging stations that match the vehicle battery model is selected and pushed to the user as the optimal route.

[0065] Compared with the prior art, the present invention has the following beneficial effects: 1. When the present invention is in use, the battery monitoring module monitors the battery status and sends the battery remaining power Qc and capacity Qn to the central control module, which sends them to the energy recovery decision module. The energy recovery decision module determines whether to recover the battery energy based on the battery remaining power Qc and battery capacity Qn. The central control module predicts the vehicle mileage S based on the battery remaining power Qc, and the travel prediction module predicts and calculates the vehicle mileage based on the battery remaining power Qc. , the travel prediction module combines the vehicle mileage S with the vehicle mileage Compare and determine the final estimated mileage of the vehicle , and the estimated mileage of the vehicle Upload to the route planning module for driving route planning, and the charging station screening module then screens out charging stations that match the vehicle battery model according to the route in the route planning module;

[0066] 2. The present invention realizes real-time monitoring of the battery and can formulate the degree of energy recovery according to the remaining battery power Qc of the battery. The present invention adds a travel prediction module to predict the vehicle mileage according to the remaining battery power Qc of the vehicle. Perform prediction calculations and compare them with the vehicle mileage S automatically predicted by the central control module to improve vehicle mileage The accuracy of the prediction, and the charging station screening module of the present invention can be based on the predicted vehicle mileage Select the best route for your vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0068] Figure 1 The present invention is a connection block diagram of a new energy vehicle power intelligent monitoring system based on the Internet of Things.

[0069] Figure 2 It is a schematic block diagram of a battery monitoring module of the present invention.

[0070] Figure 3 It is a connection block diagram of the energy recovery decision module of the present invention.

[0071] Figure 4 It is a schematic block diagram of the travel prediction module of the present invention.

[0072] Figure 5 It is a schematic diagram of the departure point A to the destination B of the present invention.

[0073] The numbers in the figure represent: 1. Central control module; 2. Battery monitoring module; 21. Battery; 22. Current sensor; 23. Voltage sensor; 24. Temperature sensor; 3. Energy recovery decision module; 31. Pedal opening sensor; 32. Motor controller; 33. Inverter; 34. Motor; 35. Power converter; 36. Decision unit; 4. Trip prediction module; 41. GPS locator; 42. High-definition camera; 43. Vehicle speed sensor; 44. Mileage prediction unit; 5. Route planning module; 6. Charging station screening module; 7. Touch screen; 8. Communication module; 9. Charging station management system; 10. Charging station. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0075] Embodiment 1: In some embodiments, please refer to the drawings of the specification Figure 1-Figure 5 , an intelligent monitoring system for electric power of new energy vehicles based on the Internet of Things, including a central control module 1, and also including the following components;

[0076] Battery monitoring module 2, used to collect the current, voltage, temperature, and remaining power of the battery 21 and battery capacity Qn and upload them to the central control module 1, which then calculates the remaining power The vehicle mileage S is automatically predicted based on the energy consumption per unit mileage E;

[0077]

[0078] Where E is the amount of electricity consumed by the vehicle per unit time, in KWh / km; Unit: KWh;

[0079] An energy recovery decision module 3, used to recover excess kinetic energy released by the vehicle during braking or coasting, and convert the kinetic energy into electrical energy and store it in a battery 21;

[0080] The travel prediction module 4 is used to receive the remaining power of the battery 21 Data information and calculate the predicted vehicle mileage , and the vehicle mileage Send to route planning module 5;

[0081] Route planning module 5, receiving and planning a driving route, and sending the driving route to the charging station screening module 6;

[0082] A charging station screening module 6 receives a driving route and screens out charging stations 10 that match the model of the vehicle battery 21 in the driving route;

[0083] A touch screen 7, which is fixedly mounted on the upper end of the vehicle center console and is used for the user to manually input the destination B;

[0084] The charging station management system 9 is connected to the central control module 1 through the communication module 8, and the central control module 1 transmits the data information of the driving route to the charging station management system 9 through the communication module 8;

[0085] The communication module 8 adopts an Internet of Things communication module.

[0086] The central control module 1 is electrically connected to the battery monitoring module 2 , the energy recovery decision module 3 , the touch screen 7 , and the communication module 8 . The communication module 8 is wirelessly connected to the charging station management system 9 , and the charging station management system 9 is wirelessly connected to the charging station 10 .

[0087] When the present invention is in use, the battery monitoring module 2 monitors the state of the battery 21, and sends the remaining power Qc and capacity Qn of the battery 21 to the central control module 1, and the central control module 1 sends it to the energy recovery decision module 3, and the energy recovery decision module 3 determines whether to recover the energy of the battery 21 according to the remaining power Qc and the battery capacity Qn of the battery, and the central control module 1 predicts the vehicle mileage S according to the remaining power Qc of the battery 21, and the travel prediction module 4 predicts and calculates the vehicle mileage according to the remaining power Qc of the battery 21. The travel prediction module 4 combines the vehicle mileage S with the vehicle mileage Compare and determine the final estimated mileage of the vehicle , and the estimated mileage of the vehicle The route is uploaded to the route planning module 5 for driving route planning, and the charging station screening module 6 then screens out the charging stations 10 that match the model of the vehicle battery 21 according to the route in the route planning module 5;

[0088] The present invention realizes real-time monitoring of the battery 21, and can formulate the degree of energy recovery according to the remaining power Qc of the battery 21. The present invention adds a travel prediction module 4 to predict the vehicle mileage according to the remaining power Qc of the vehicle battery 21. The prediction calculation is performed and compared with the vehicle mileage S automatically predicted by the central control module 1, thereby improving the vehicle mileage The accuracy of the prediction, and the charging station screening module 6 of the present invention can be based on the predicted vehicle mileage Select the best route for your vehicle.

[0089] Embodiment 2: In some embodiments, Figure 2 , Figure 3 and Figure 4 As shown, as a preferred embodiment of the present invention, the battery monitoring module 2 includes a battery 21, a current sensor 22, a voltage sensor 23 and a temperature sensor 24, the current sensor 22 and the voltage sensor 23 are electrically connected to the battery 21, the temperature sensor 24 is fixedly installed on the battery 21, the current sensor 22, the voltage sensor 23, the temperature sensor 24 are electrically connected to the battery 21, the battery 21 is connected to the energy recovery decision module 3, and the battery 21 is electrically connected to the central control module 1.

[0090] The energy recovery decision module 3 includes a pedal opening sensor 31, a motor controller 32, an inverter 33, a motor 34 and a power converter 35. The pedal opening sensor 31 is electrically connected to the motor controller 32, the motor controller 32 is electrically connected to the inverter 33, the inverter 33 is electrically connected to the motor 34, the motor 34 is electrically connected to the power converter 35 and the battery 21, and the pedal opening sensor 31 and the motor controller 32 are electrically connected to the central control module 1.

[0091] The pedal opening sensor 31 collects the pedal opening information and transmits the opening information to the central control module 1. The central control module 1 receives the pedal opening information and determines whether the opening information is greater than the opening value set in the system. If the central control module 1 determines that the pedal opening information is greater than the opening value set in the system, the central control module 1 controls the motor controller 32 to start, the motor controller 32 controls the inverter 33 to start, the inverter 33 controls the motor 34 to start, the battery 21 supplies power to the motor 34 through the power converter 35, and the motor 34 provides power to the vehicle;

[0092] If the central control module 1 determines that the pedal opening information is less than the opening value set in the system, the vehicle is in a braking or coasting state, and the motor 34 will be converted into a generator, converting the kinetic energy during the coasting process into electrical energy and storing it in the battery 21.

[0093] The energy recovery decision module 3 also includes a decision unit 36, which receives the remaining power collected by the central control module 1. Set the energy recovery value ;

[0094]

[0095] According to the SOC value, the decision unit 36 ​​determines whether to perform energy recovery:

[0096] When SOC>0.8, the decision unit 36 ​​does not perform energy recovery;

[0097] When 0.7≤SOC≤0.8, the decision unit 36 ​​performs energy recovery, and the current of the energy recovery is less than the maximum charging current allowed by the battery (21);

[0098] When SOC<0.7, the decision unit 36 ​​performs energy recovery, and the current of energy recovery is not affected by the maximum charging current allowed by the battery (21).

[0099] The travel prediction module 4 includes a GPS locator 41, a high-definition camera 42 and a vehicle speed sensor 43. The GPS locator 41 and the high-definition camera 42 are fixedly installed inside the vehicle, and the vehicle speed sensor 43 is fixedly installed at the wheel; the GPS locator 41, the high-definition camera 42 and the vehicle speed sensor 43 are all electrically connected to the central control module 1.

[0100] The travel prediction module 4 further includes a mileage prediction unit 44 , which is used to receive data information from a GPS locator 41 , a high-definition camera 42 , and a vehicle speed sensor 43 .

[0101] In order to improve the accuracy of the prediction, the mileage prediction unit 44 predicts the vehicle mileage in the following steps:

[0102] Step 1: The calculation formula for the energy consumption per unit mileage of the vehicle is:

[0103]

[0104] E is the energy consumption per unit mileage, kW·h / km; P is the power demand during driving, kW; is the driving distance, km; is the travel time, h;

[0105] Step 2: Power requirements during driving at a constant speed for:

[0106]

[0107] is the power demand, v is the uniform vehicle speed, km / h; C is the drag coefficient; A is the vehicle's frontal area, ; is the slope; f is the rolling resistance coefficient, N / kN; For electric drive efficiency; is the weight of the vehicle, kg; is the acceleration due to gravity;

[0108] Will Substituting into E, the energy consumption per unit mileage when the vehicle is traveling at a constant speed is :

[0109]

[0110] Step 3: Vehicle acceleration and power requirements during driving for:

[0111]

[0112] For power demand; is vehicle speed, km / h; is the vehicle rotation mass conversion factor; is the acceleration;

[0113] Will Substituted into E, the energy consumption per unit mileage when the vehicle accelerates for:

[0114]

[0115] In the formula, is the acceleration starting speed, km / h; is the acceleration end speed, km / h;

[0116] Step 4: The mileage energy consumption of the vehicle in the combination of constant speed driving and accelerated driving is , unit: kW.h;

[0117] Step 5: During braking, the energy recovered by the battery 21 is :

[0118]

[0119] N is the number of braking times, is the braking time;

[0120] Step 6: Assume that the energy of battery 21 before departure is , and the remaining total energy of the vehicle battery is obtained for:

[0121] The driving range can be obtained from this , unit km;

[0122]

[0123] The mileage prediction unit 44 calculates Compare with the mileage S predicted by the system:

[0124] like When , as the estimated mileage of the vehicle ;

[0125] like When , as the estimated mileage of the vehicle ;

[0126] like When , take S as the estimated mileage of the vehicle .

[0127] Embodiment 3: In some embodiments, Figure 4 , Figure 5 As shown in the figure, as a preferred embodiment of the present invention, the route planning module 5 receives the remaining mileage of the vehicle predicted by the mileage prediction unit 44. , plan a route to destination B;

[0128] The planning steps are as follows:

[0129] Step 1: The user inputs the destination B in the touch screen 7, and the touch screen 7 uploads the destination to the central control module 1, and the central control module 1 first plans multiple routes from the departure point A to the destination B;

[0130] Step 2: The central control module 1 receives the vehicle mileage predicted by the mileage prediction unit 44 , and determine whether the vehicle can reach destination B;

[0131] Step 3: The central control module 1 determines the shortest route from the departure point A to the destination B. Vehicle mileage the relationship between;

[0132] like , then the central control module 1 selects the route Push it to users as the optimal route;

[0133] like , the central control module 1 sends all the planned routes to the charging station screening module 6 , and the charging station screening module 6 performs screening and judgment of the charging stations 10 .

[0134] The steps of the charging station screening module 6 screening the route information containing the charging station 10 are as follows:

[0135] Step 1: The charging station management system 9 uploads the location information and data information of the charging stations 10 within 2 kilometers of the battery monitoring module of the destination B to the charging station screening module 6;

[0136] Step 2: If there is a charging station 10 within 2 km of destination B and the charging station 10 within 2 km of destination B matches the vehicle charging current, the charging station screening module 6 directly screens out the route Push it to users as the optimal route;

[0137] Step 3: If there is no charging station 10 within 2 kilometers of the destination B, or the charging station 10 within 2 kilometers of the destination B does not match the vehicle battery 21 model, the charging station screening module 6 will perform route screening;

[0138] Step 4: The charging station screening module 6 screens out the routes that contain the charging station 10 from the routes planned by the route planning module 5. The charging station screening module 6 screens out the charging station 10 that matches the model of the vehicle battery 21 from the routes that contain the charging station 10; finally, the shortest route that contains the charging station 10 that matches the model of the vehicle battery 21 is screened out and pushed to the user as the optimal route.

[0139] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will 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. An intelligent monitoring system for electric power of new energy vehicles based on the Internet of Things, comprising a central control module (1), characterized in that: Also includes the following components; A battery monitoring module (2) is used to collect the current, voltage, temperature, and remaining power of the battery (21). and battery capacity Qn and uploaded to the central control module (1), which then calculates the remaining power The vehicle mileage S is automatically predicted based on the energy consumption per unit mileage E; An energy recovery decision module (3) is used to recover excess kinetic energy released by the vehicle during braking or coasting, and convert the kinetic energy into electrical energy and store it in a battery (21); A travel prediction module (4) is used to receive the remaining power of the battery (21) Data information and calculate the predicted vehicle mileage , and the vehicle mileage Send to the route planning module (5); Route planning module (5), receives and planning a driving route, and sending the driving route to a charging station screening module (6); A charging station screening module (6) receives a driving route and screens out a charging station (10) that matches the model of the vehicle battery (21) in the driving route; A touch screen (7), the touch screen (7) is fixedly mounted on the upper end of the vehicle center console and is used for a user to manually input a destination B; The charging station management system (9) is connected to the central control module (1) through the communication module (8), and the central control module (1) transmits data information of the driving route to the charging station management system (9) through the communication module (8); The central control module (1) is electrically connected to the battery monitoring module (2), the energy recovery decision module (3), the touch screen (7), and the communication module (8); the communication module (8) is wirelessly connected to the charging station management system (9); and the charging station management system (9) is wirelessly connected to the charging station (10).

2. According to claim 1, the intelligent monitoring system for new energy vehicle power based on the Internet of Things is characterized in that: The battery monitoring module (2) comprises a battery (21), a current sensor (22), a voltage sensor (23) and a temperature sensor (24); the current sensor (22) and the voltage sensor (23) are both electrically connected to the battery (21); the temperature sensor (24) is fixedly mounted on the battery (21); the current sensor (22), the voltage sensor (23) and the temperature sensor (24) are both electrically connected to the battery (21); the battery (21) is connected to the energy recovery decision module (3); and the battery (21) is electrically connected to the central control module (1).

3. The new energy vehicle power intelligent monitoring system based on the Internet of Things according to claim 2 is characterized in that: The energy recovery decision module (3) comprises a pedal opening sensor (31), a motor controller (32), an inverter (33), a motor (34) and a power converter (35); the pedal opening sensor (31) is electrically connected to the motor controller (32); the motor controller (32) is electrically connected to the inverter (33); the inverter (33) is electrically connected to the motor (34); the motor (34) is electrically connected to the power converter (35) and the battery (21); and the pedal opening sensor (31) and the motor controller (32) are electrically connected to the central control module (1).

4. The new energy vehicle power intelligent monitoring system based on the Internet of Things according to claim 3 is characterized in that: The energy recovery decision module (3) further comprises a decision unit (36), which receives the remaining power collected by the central control module (1). Set the energy recovery value ; ； The decision unit (36) determines whether to perform energy recovery according to the SOC value: When SOC>0.8, the decision unit (36) does not perform energy recovery; When SOC≤0.8, the decision unit (36) performs energy recovery.

5. The new energy vehicle power intelligent monitoring system based on the Internet of Things according to claim 4 is characterized in that: The travel prediction module (4) comprises a GPS locator (41), a high-definition camera (42) and a vehicle speed sensor (43); the GPS locator (41) and the high-definition camera (42) are both fixedly installed inside the vehicle, and the vehicle speed sensor (43) is fixedly installed at the wheel; the GPS locator (41), the high-definition camera (42) and the vehicle speed sensor (43) are all electrically connected to the central control module (1).

6. The new energy vehicle power intelligent monitoring system based on the Internet of Things according to claim 5 is characterized in that: The travel prediction module (4) further comprises a mileage prediction unit (44), wherein the mileage prediction unit (44) is used to receive data information from a GPS locator (41), a high-definition camera (42), and a vehicle speed sensor (43).

7. The new energy vehicle power intelligent monitoring system based on the Internet of Things according to claim 6 is characterized in that: The mileage prediction unit (44) predicts the vehicle mileage in the following steps; Step 1: The calculation formula for the energy consumption per unit mileage of the vehicle is: ， E is the energy consumption per unit mileage, kW·h / km; P is the power demand during driving, kW; is the driving distance, km; t is the travel time, h; Step 2: Power requirements during driving at a constant speed for: ， is the power demand, v is the uniform vehicle speed, km / h; C is the drag coefficient; A is the vehicle's frontal area, ; is the slope; f is the rolling resistance coefficient, N / kN; For electric drive efficiency; is the weight of the vehicle, kg; is the acceleration due to gravity; Will Substituting into E, the energy consumption per unit mileage when the vehicle is traveling at a constant speed is : ， Step 3: Vehicle acceleration and power requirements during driving for: ， For power demand; is the vehicle speed, km / h; is the vehicle rotation mass conversion factor; is the acceleration; Will Substituted into E, the energy consumption per unit mileage when the vehicle accelerates for: ， In the formula, is the acceleration starting speed, km / h; is the acceleration end speed, km / h; Step 4: The mileage energy consumption of the vehicle in the combination of constant speed driving and accelerated driving is , unit: kW.h; Step 5: During braking, the energy recovered by the battery (21) is : ，， N is the number of braking times, is the braking time; Step 6: Assume that the energy of the battery (21) before departure is , and the remaining total energy of the vehicle battery is obtained for: , The driving range can be obtained from this , unit km; 。 8. The new energy vehicle power intelligent monitoring system based on the Internet of Things according to claim 7 is characterized in that: The mileage prediction unit (44) calculates Compare with the mileage S predicted by the system: like When , as the estimated mileage of the vehicle ; like When , as the estimated mileage of the vehicle ; like When , take S as the estimated mileage of the vehicle .

9. The new energy vehicle power intelligent monitoring system based on the Internet of Things according to claim 8 is characterized in that: The route planning module (5) receives the remaining mileage of the vehicle predicted by the mileage prediction unit (44). , the route planning module (5) plans a route to the destination B; The planning steps are as follows: Step 1: The user inputs the destination B on the touch screen (7), and the touch screen (7) uploads the destination to the central control module (1). The central control module (1) first plans a plurality of routes from the departure point A to the destination B; Step 2: The central control module (1) receives the vehicle mileage predicted by the mileage prediction unit (44) , and determine whether the vehicle can reach destination B; Step 3: The central control module (1) determines the shortest route from the vehicle’s departure point A to its destination B. Vehicle mileage the relationship between; like , then the central control module (1) selects the route Push it to users as the optimal route; like , the central control module (1) sends all the planned multiple routes to the charging station screening module (6), and the charging station screening module (6) performs screening and judgment of the charging stations (10).

10. The new energy vehicle power intelligent monitoring system based on the Internet of Things according to claim 9 is characterized in that: The steps of the charging station screening module (6) screening the route information containing the charging station (10) are as follows: Step 1: The charging station management system (9) uploads the location information and data information of the charging stations (10) within a kilometer of the battery monitoring module (2) of the destination B to the charging station screening module (6); Step 2: If there is a charging station (10) within 2 kilometers of destination B and the charging station (10) within 2 kilometers of destination B matches the vehicle charging current, the charging station screening module (6) directly screens out the route Push it to users as the optimal route; Step 3: If there is no charging station (10) within 2 kilometers of the destination B, or the charging station (10) within 2 kilometers of the destination B does not match the model of the vehicle battery (21), the charging station screening module (6) will perform route screening; Step 4: The charging station screening module (6) screens out the routes that contain the charging stations (10) from the routes planned by the route planning module (5), and the charging station screening module (6) screens out the charging stations (10) that match the model of the vehicle battery (21) from the routes that contain the charging stations (10); finally, the shortest route that contains the charging stations (10) that match the model of the vehicle battery (21) is screened out and pushed to the user as the optimal route.

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