KR102527860B1 - Method And Apparatus for Analyzing Energy Harvesting Power Generation - Google Patents

Abstract

An energy harvesting power generation analysis method and apparatus are disclosed.
In this embodiment, for energy harvesting of a sensor mounted on a vehicle, the amount of energy harvesting is calculated based on the energy source according to vibration, temperature, and vehicle speed measured during actual driving, the initial charging voltage, and the load power of each connected sensor node. Provided is an energy harvesting power generation analysis method and device that predicts and analyzes.

Description

Method and apparatus for analyzing energy harvesting power generation {Method And Apparatus for Analyzing Energy Harvesting Power Generation}

One embodiment of the present invention relates to a method and apparatus for analyzing energy harvesting power generation.

The contents described below merely provide background information related to the present embodiment and do not constitute prior art.

Most of the electricity is generated in power generation facilities and supplied to users. When generating electricity, power generation facilities consume various types of fuel, which creates pollutants. Reducing the use of traditional power generation facilities can suppress the generation of pollutants, so in order to create a cleaner environment, many studies are being conducted on environmentally friendly power generation methods that can generate power without fuel.

As a nature-friendly power generation method, a method using natural power such as wind power, solar power, and wave power is widely known. In addition, relatively recently, a new technical concept has been in the limelight. That is, even small-scale electricity is spreading the awareness that it is very useful to store it frequently and use it when necessary if it can be obtained naturally in daily life, and a method for technically implementing this is being studied. This technical concept is commonly known as energy harvesting.

Energy harvesting has a problem that is difficult to standardize in a specific way.

In this embodiment, for energy harvesting of a sensor mounted on a vehicle, the amount of energy harvesting is calculated based on the energy source according to vibration, temperature, and vehicle speed measured during actual driving, the initial charging voltage, and the load power of each connected sensor node. An object of the present invention is to provide a method and apparatus for predicting and analyzing energy harvesting power generation.

According to one aspect of this embodiment, a measurement unit installed in a vehicle to measure a plurality of energy sources generated from the vehicle; a collection unit for collecting and delivering a plurality of the energy sources; a monitoring unit for monitoring the plurality of energy sources in real time; And matching the energy harvesting data obtained by converting the plurality of energy sources into numerical values for each energy source, and generating generation prediction data for predicting the generation amount for each energy source based on the energy harvesting data matched for each energy source, It provides an energy harvesting power generation analysis device comprising a; prediction unit for calculating power generation efficiency based on the power generation prediction data.

As described above, according to the present embodiment, for energy harvesting of a sensor mounted on a vehicle, the amount of energy harvesting is generated based on an energy source according to vibration, temperature, and vehicle speed measured during actual driving and the load of the connected sensor node. There is an effect that can be analyzed by predicting.

In this embodiment, it is installed in a vehicle, and after measuring vibration, temperature, and speed generated in the vehicle, there is an effect of accurately predicting how much power generation is required.

In this embodiment, it is installed in a vehicle, and it is possible to check how much energy is generated according to vibration, temperature, and speed generated in the vehicle, and to accurately predict the total usable energy amount by summing the energy amount.

1 is a diagram showing an energy harvesting generation amount analyzer measuring a vehicle energy source according to an exemplary embodiment.
2 is a diagram showing a measurement unit, a collection unit, and a prediction unit in detail according to the present embodiment.
3 is a diagram showing an energy harvester (EH) power generation prediction model according to this embodiment.
4 is a diagram showing a real-time energy source monitoring screen according to the present embodiment.

Hereinafter, this embodiment will be described in detail with reference to the accompanying drawings.

1 is a diagram showing an energy harvesting generation amount analyzer measuring a vehicle energy source according to an exemplary embodiment.

The energy harvesting generation amount analyzer 100 harvests energy and stores self-driving power of a sensor attached to a vehicle (eg, a truck). The energy harvesting generation amount analyzer 100 measures an energy source generated from a vehicle. The energy harvesting generation amount analyzer 100 converts the measured energy sources into energy harvesting data (actual data) converted into actual values.

The energy harvesting generation amount analyzer 100 matches the converted energy harvesting data converted into actual numerical values for each energy source. The energy harvesting power generation analyzer 100 predicts power generation for each energy source and calculates power generation efficiency when converted energy harvesting data converted into actual numerical values is input.

The energy harvesting generation amount analyzer 100 may indicate that the predicted generation amount is insufficient based on the converted energy harvesting data converted into actual values. When displacement data is measured from the vibration displacement measurement sensor 210, the energy harvesting generation amount analyzer 100 collects the displacement data.

The energy harvesting power generation analysis device 100 converts the data collected using the predictive model into actual values, and converts the converted data (eg, when the temperature is 100 ° C, energy that can be harvested based on 100 ° C) Based on this, the amount of energy that can be harvested is matched.

The energy harvesting generation amount analyzer 100 uses most of the harvested energy for power supply. The energy harvesting generation amount analyzer 100 may provide additional information by adding harvested energy to the current amount of charge and available power.

The energy harvesting generation amount analyzer 100 is a method of measuring and then collecting energy sources, and is preferably applicable to trucks, but is not necessarily limited thereto.

The energy harvesting generation amount analyzer 100 predicts the amount of power generation based on temperature, vibration, and vehicle speed to actually check how much energy source is coming in, and predicts how much output according to the energy source is It can be reflected in the development of energy generation equipment.

The energy harvesting power generation analyzer 100 performs energy harvesting based on values of vibration, temperature, and vehicle wheel speeds sensed, and predicts power generation based on the energy harvesting values.

The energy harvesting generation amount analyzer 100 is installed in a vehicle and must first perform a measurement step for each vibration, temperature, and speed generated in the vehicle, and then accurately predict how much power generation is required. The energy harvesting power generation analysis device 100 checks how much energy is generated according to vibration, temperature, and speed generated in the vehicle, and generates power generation prediction data by estimating the total usable energy by adding the energy.

The energy harvesting generation amount analyzer 100 checks the amount of stored energy and then checks the energy consumption pattern of how much power the system intends to consume compared to the amount of stored energy.

The energy harvesting generation amount analyzer 100 checks an energy consumption pattern at a preset period (eg, 1 minute). The energy harvesting generation amount analyzer 100 checks the ratio of the stored energy to the energy used for running the entire section (eg, 100 km), and calculates the energy use time and the amount of remaining energy. The energy harvesting generation amount analyzer 100 calculates the available driving time based on the energy usage time and the amount of remaining energy.

The energy harvesting generation amount analysis device 100 digitizes the amount of power generation according to the previously tested vibration displacement deviation, converts it into a database as back data, and stores it in the vibration energy harvesting database. The energy harvesting generation amount analyzer 100 compares the information stored in the vibration energy harvesting database with currently confirmed vibration harvesting data to predict an output according to vibration displacement.

The energy harvesting generation amount analysis device 100 digitizes the amount of power generation according to the previously tested temperature deviation, converts it into a database as back data, and stores it in the thermoelectric energy harvesting database. The energy harvesting generation amount analyzer 100 compares information stored in a thermoelectric energy harvesting database with currently identified thermoelectric harvesting data to predict output according to temperature.

The energy harvesting generation amount analysis device 100 digitizes the amount of power generation according to the previously tested wheel speed deviation, converts it into a database as back data, and stores it in the eddy current energy harvesting database. The energy harvesting generation amount analyzer 100 compares information stored in the eddy current energy harvesting database with currently identified wheel rotation harvesting data to predict an output according to wheel rotation speed.

The energy harvesting generation amount analyzer 100 checks a temperature difference between the thermoelectric material and the heat sink using the temperature sensor 220 . When measuring the temperature using the temperature measuring sensor 220, the energy harvesting power generation analyzer 100 checks the time the temperature is maintained according to the elapsed time even if the temperature changes due to the vehicle speed. The energy harvesting generation amount analyzer 100 predicts the amount of power generation according to the maintained time.

The energy harvesting generation amount analyzer 100 may calculate how much power is generated and how much load can be operated based on the available generation amount.

The energy harvesting generation amount analyzer 100 measures the vibration variation and performs vibration energy harvesting. The energy harvesting generation amount analyzer 100 measures the temperature and performs thermoelectric energy harvesting. The energy harvesting generation amount analyzer 100 measures wheel rotation speed to perform vehicle speed energy harvesting. The energy harvesting generation amount analyzer 100 determines the amount of output according to the wheel rotation speed.

The energy harvesting generation amount analyzer 100 collects a vehicle location using a GPS module to determine a vehicle speed. The energy harvesting generation amount analyzer 100 checks the rotational speed of the wheel based on the size of the wheel, and checks the moving distance difference between locations based on GPS information. The energy harvesting generation amount analyzer 100 calculates the rotation speed per minute based on the wheel rotation speed and the distance difference.

When performing different energy harvesting, the energy harvesting generation amount analyzer 100 checks the actual generation amount and the conversion efficiency of the stored energy according to each energy collection method.

The energy harvesting generation amount analyzer 100 applies a preset weight according to each harvesting characteristic according to different energy harvesting methods. The energy harvesting generation amount analyzer 100 sums data obtained by applying each harvesting characteristic as a weight.

The energy harvesting generation amount analyzer 100 applies a weight according to energy efficiency when converting the collected energy sources, excluding values exceeding a threshold according to the conversion level, and converting the remaining balance.

The energy harvesting generation amount analyzer 100 checks the current input to the power line using the harvesting model, and harvests the eddy current energy according to the current characteristics. When the energy harvesting generation amount analyzer 100 combines the stored eddy current energies, a weight value according to energy efficiency is reflected for each remaining value except for a value exceeding a threshold value.

The energy harvesting generation amount analyzer 100 determines whether the usable amount of power is imbalanced or normal operation using the collected amount of power compared to the current amount of charge.

The energy harvesting generation amount analyzer 100 according to the present embodiment includes a measuring unit 110, a collecting unit 120, and a predicting unit 130. Components included in the energy harvesting generation amount analyzer 100 are not necessarily limited thereto.

Each component included in the energy harvesting generation amount analyzer 100 is connected to a communication path connecting a software module or a hardware module inside the device and may operate organically with each other. These components communicate using one or more communication buses or signal lines.

Each component of the energy harvesting power generation analyzer 100 shown in FIG. 1 means a unit that processes at least one function or operation, and may be implemented as a software module, a hardware module, or a combination of software and hardware. there is.

The measuring unit 110 is installed in a vehicle and measures a plurality of energy sources generated from the vehicle. The measuring unit 110 includes a vibration displacement measuring sensor 210 , a temperature measuring sensor 220 , and a vehicle speed measuring sensor 230 .

The collection unit 120 collects and delivers a plurality of energy sources. The collection unit 120 includes a vibration displacement data collection unit 212 , a temperature data collection unit 222 , and a vehicle speed data collection unit 232 .

The prediction unit 130 analyzes and calculates data with a program using DAQ (Data Acquisition) to predict energy harvesting power generation. The prediction unit 130 calculates the load sensor power consumption and the initial battery charging voltage according to the operation pattern based on the predicted output of each energy harvester according to the input energy source. The prediction unit 130 finally determines the operating state of the sensor according to the input displacement, predicts the energy harvester output level, remaining battery capacity and time, and the like.

The prediction unit 130 builds a wheel rotational energy database according to the acquired vibration displacement, heat, and vehicle speed of the vehicle. The prediction unit 130 generates an energy harvester prediction model based on the database. The prediction unit 130 predicts the amount of power generation using an energy harvester prediction model. The prediction unit 130 reflects the energy harvester design according to the level of the energy source during actual driving of the vehicle.

The prediction unit 130 includes a vibration energy harvesting power generation prediction model 214 , a thermoelectric energy harvesting power generation prediction model 224 , and an eddy current energy harvesting power generation prediction model 234 .

The prediction unit 130 matches energy harvesting data obtained by converting a plurality of energy sources into numerical values for each energy source. The prediction unit 130 generates generation amount prediction data by predicting the amount of power generation for each energy source based on the energy harvesting data matched for each energy source. The prediction unit 130 calculates power generation efficiency based on the power generation prediction data.

The prediction unit 130 calculates the energy use time and remaining energy amount of the entire section by reflecting the predicted amount of power generation based on the prediction data of the amount of power generation as the necessary energy required for the entire preset section. The prediction unit 130 calculates the available driving time based on the energy usage time and the amount of remaining energy.

The prediction unit 130 predicts the current battery charge amount by adding the power amount corresponding to the generation amount prediction data to the current charge amount. The predictor 130 checks power consumption for each energy source consumed from the current battery charge amount and then calculates an energy consumption pattern for each energy source.

2 is a diagram showing a measurement unit, a collection unit, and a prediction unit in detail according to the present embodiment.

The vibration displacement measuring sensor 210 measures vibration displacement of the vehicle's suspension, leaf spring, etc. while driving. The vibration displacement measuring sensor 210 measures a vibration range from a leaf spring of a vehicle suspension. The vibration displacement measuring sensor 210 generates vibration displacement data obtained by measuring a vibration range from a leaf spring of a suspension of a vehicle.

The temperature measuring sensor 220 measures the air temperature of the exhaust port of the vehicle and its surroundings. The temperature measurement sensor 220 generates temperature data for measuring the air temperature around the exhaust vent of the vehicle and the exhaust vent.

The vehicle speed measurement sensor 230 includes a GPS sensor unit that measures the speed and position of the vehicle. The vehicle speed measurement sensor 230 measures the speed of the wheels of the vehicle and generates vehicle speed data obtained by measuring a distance difference according to the vehicle position.

The vibration displacement data collection unit 212 collects vibration displacement data from the vibration displacement measuring sensor 210 during a predetermined period.

The temperature data collection unit 222 collects temperature data from the temperature sensor 220 during a certain period.

The vehicle speed data collection unit 120 collects vehicle speed data from the vehicle speed measurement sensor 230 during a predetermined period.

The vibration energy harvesting power generation prediction model 214 converts acceleration, displacement, and frequency into numerical values based on vibration displacement data, and predicts power generation according to output based on the converted values.

The vibration energy harvesting power generation prediction model 214 converts acceleration, displacement, frequency, etc. into information based on vibration displacement data, and then predicts output using the vibration displacement energy harvesting prediction model.

The vibration energy harvesting power generation prediction model 214 analyzes the amplitude and frequency based on the displacement data and predicts the generated power through matching with the output database of the vibration energy harvester for each input vibration.

The vibration energy harvesting power generation prediction model 214 analyzes the acceleration and amplitude of the suspension based on the vibration displacement data. The vibration energy harvesting power generation prediction model 214 matches the vibration energy harvesting database based on the load of the acceleration, amplitude, and vibration displacement measuring sensors. The vibration energy harvesting power generation prediction model 214 calculates a vibration energy harvesting output by performing an operation based on the vibration energy harvesting database and matched acceleration, amplitude, and vibration displacement measuring sensors.

The vibration energy harvesting power generation prediction model 214 multiplies the vibration energy harvesting output by time to calculate the vibration energy harvesting value. The vibration energy harvesting power generation prediction model 214 calculates a vibration energy battery charging value by adding an initial charging voltage to a vibration energy harvesting value. The vibration energy harvesting generation amount prediction model 214 calculates the current battery charge amount by subtracting the vibration sensor load power from the vibration energy battery charge value.

The thermoelectric energy harvesting power generation prediction model 224 converts the temperature of the exhaust port and ambient air temperature into numerical values based on the temperature data, and then predicts the amount of power generation according to the output based on the converted values.

The thermoelectric energy harvesting power generation prediction model 224 converts the temperature into information based on the temperature data, and then predicts the output using the thermoelectric energy harvesting prediction model. The thermoelectric energy harvesting power generation prediction model 224 predicts generated power by matching the exhaust temperature and air temperature included in the temperature data with the input temperature and the efficiency according to the temperature difference and the output database.

The thermoelectric energy harvesting power generation prediction model 224 checks the exhaust temperature, ambient air temperature, and temperature difference (ΔT) based on the temperature data. The thermoelectric energy harvesting power generation prediction model 224 matches the thermoelectric energy harvesting database based on the exhaust temperature, the ambient air temperature, and the temperature difference ΔT. The thermoelectric energy harvesting power generation prediction model 224 calculates a temperature energy harvesting output based on the exhaust temperature matched to the thermoelectric energy harvesting database, the ambient air temperature, and the temperature difference ΔT.

The thermoelectric energy harvesting power generation prediction model 224 multiplies the temperature energy harvesting output by time to calculate the temperature energy harvesting value. The thermoelectric energy harvesting generation amount prediction model 224 calculates a temperature energy battery charge value obtained by adding an initial charge voltage to a temperature energy harvesting value. The thermoelectric energy harvesting generation amount prediction model 224 calculates the current battery charge amount by subtracting the temperature sensor load power from the temperature energy battery charge value.

The eddy current energy harvesting power generation prediction model 234 converts acceleration, wheel speed, and distance difference according to vehicle position into numerical values based on vehicle speed data, and predicts power generation according to output based on the converted values.

The eddy current energy harvesting generation amount prediction model 234 converts acceleration, wheel speed, position, etc. into information based on vehicle speed data, and then predicts output using the eddy current energy harvesting prediction model. The eddy current energy harvesting power generation prediction model 234 calculates the rotation speed according to the wheels of the mounted vehicle using the vehicle speed data. The eddy current energy harvesting power generation prediction model 234 predicts the output by matching with the output database of the eddy current energy harvester according to the rotation speed of the non-magnetic surface of the wheel using the rotation speed.

The eddy current energy harvesting power generation prediction model 234 checks the wheel rotational speed based on the measured vehicle speed and wheel size. The eddy current energy harvesting power generation prediction model 234 matches the eddy current energy harvesting database based on the wheel rotation speed. The eddy current energy harvesting generation amount prediction model 234 calculates a vehicle speed energy harvesting output based on a wheel rotation speed and eddy current matched with an eddy current energy harvesting database.

The eddy current energy harvesting power generation prediction model 234 multiplies the vehicle speed energy harvesting output by time to calculate the vehicle speed energy harvesting value. The eddy current energy harvesting generation amount prediction model 234 calculates a vehicle speed energy battery charging value by adding an initial charging voltage to a vehicle speed energy harvesting value. The eddy current energy harvesting generation amount prediction model 234 calculates the current battery charge amount by subtracting the vehicle speed sensor load power from the vehicle speed energy battery charge value.

The monitoring unit 250 monitors a plurality of energy sources in real time. The monitoring unit 250 outputs vibration displacement data, temperature data, and vehicle speed measurement data in the form of a graph of amplitude over time.

3 is a diagram showing an energy harvester (EH) power generation prediction model according to this embodiment.

The vibration energy harvesting power generation prediction model 214 includes a vibration displacement data collection module 312, a vibration analysis module 314, a displacement matching module 316, and a displacement diagnosis module 318.

The vibration displacement data collection module 312 collects vibration displacement data from the vibration displacement data collection unit 212 . The vibration analysis module 314 analyzes acceleration and amplitude based on the input vibration displacement data. The displacement matching module 316 matches the vibration energy harvesting database based on acceleration, amplitude, and sensor load.

The displacement diagnosis module 318 diagnoses the state of charge of the battery by performing calculations on the acceleration, amplitude, and sensor load matched with the vibration energy harvesting database. The displacement diagnosis module 318 diagnoses the state of charge of the battery using [Equation 1].

The displacement diagnosis module 318 calculates a vibration energy harvesting value obtained by multiplying the vibration energy harvesting output by time. The displacement diagnosis module 318 calculates the vibration energy battery charging value by adding the initial charging voltage to the vibration energy harvesting value. The displacement diagnosis module 318 calculates the current battery charge amount by subtracting the vibration sensor load power from the charge value of the vibration energy battery.

The thermoelectric energy harvesting power generation prediction model 224 includes a temperature data collection module 332 , a temperature calculation module 324 , a temperature matching module 326 , and a temperature diagnosis module 328 .

The temperature data collection module 332 collects temperature data from the temperature data collection unit 222 . The temperature calculation module 324 calculates a temperature difference ΔT between the exhaust port temperature and ambient air temperature based on the temperature data. The temperature matching module 326 matches the exhaust port temperature, ambient air temperature, and temperature difference criteria with a thermoelectric energy harvesting database.

The temperature diagnosis module 328 diagnoses the state of charge of the battery based on the exhaust temperature matched to the thermoelectric energy harvesting database, ambient air temperature, and temperature difference criteria. The temperature diagnosis module 328 diagnoses the state of charge of the battery using [Equation 2].

The temperature diagnosis module 328 calculates a temperature energy harvesting value obtained by multiplying the temperature energy harvesting output by time. The temperature diagnosis module 328 calculates a temperature energy battery charge value obtained by adding the initial charge voltage to the temperature energy harvesting value. The temperature diagnosis module 328 calculates the current battery charge amount by subtracting the temperature sensor load power from the temperature energy battery charge value.

The eddy current energy harvesting generation amount prediction model 234 includes a vehicle speed data collection module 332 , a wheel rotation speed calculation module 334 , a vehicle speed matching module 336 , and a vehicle speed diagnosis module 338 .

The vehicle speed data collection module 332 collects vehicle speed data from the vehicle speed data collection unit 232 . The wheel rotation speed calculation module 334 calculates the wheel rotation speed through the measured vehicle speed and wheel size. The vehicle speed matching module 336 matches the wheel rotation speed with an eddy current energy harvesting database.

The vehicle speed diagnosis module 338 diagnoses the state of charge of the battery based on the wheel rotational speed and eddy current matched with an eddy current energy harvesting database. The vehicle speed diagnosis module 338 diagnoses the state of charge of the battery using [Equation 3].

The vehicle speed diagnosis module 338 calculates a vehicle speed energy harvesting value obtained by multiplying the vehicle speed energy harvesting output by time. The vehicle speed diagnosis module 338 calculates a vehicle speed energy battery charge value obtained by adding an initial charge voltage to a vehicle speed energy harvesting value. The vehicle speed diagnosis module 338 calculates the current battery charge amount by subtracting the vehicle speed sensor load power from the vehicle speed energy battery charge value.

4 is a diagram showing a real-time energy source monitoring screen according to the present embodiment.

The monitoring unit 250 collects vibration data, temperature data, and vehicle speed data from the measuring unit 110 . The monitoring unit 250 monitors vibration data, temperature data, and vehicle speed data collected using the real-time energy source monitoring module.

As shown in FIG. 4 , the monitoring unit 250 monitors the suspension displacement in the form of a graph with an amplitude over time based on the vibration data.

The monitoring unit 250 monitors the exhaust port temperature in the form of a graph with an amplitude over time based on the temperature data. The monitoring unit 250 monitors the vehicle speed in the form of a graph with an amplitude over time based on the vehicle speed data.

The above description is merely an example of the technical idea of the present embodiment, and various modifications and variations can be made to those skilled in the art without departing from the essential characteristics of the present embodiment. Therefore, the present embodiments are not intended to limit the technical idea of the present embodiment, but to explain, and the scope of the technical idea of the present embodiment is not limited by these embodiments. The scope of protection of this embodiment should be construed according to the claims below, and all technical ideas within the scope equivalent thereto should be construed as being included in the scope of rights of this embodiment.

100: energy harvesting power generation analyzer
110: measuring unit
120: collection unit
130: prediction unit
250: monitoring unit

Claims (13)

a measurement unit installed in a vehicle to measure a plurality of energy sources generated from the vehicle;
a collection unit for collecting and delivering a plurality of the energy sources;
a monitoring unit for monitoring a plurality of the energy sources in real time; and
Energy harvesting data obtained by converting a plurality of the energy sources into numerical values is matched for each energy source, and based on the energy harvesting data matched for each energy source, generation amount prediction data is generated by predicting the amount of power generation for each energy source. A prediction unit for calculating power generation efficiency based on power generation prediction data; including,
The measuring unit,
a vibration displacement measuring sensor for generating vibration displacement data obtained by measuring a vibration range from a leaf spring of the suspension of the vehicle;
a temperature measurement sensor configured to generate temperature data for measuring the air temperature of the exhaust port of the vehicle and the air around the exhaust port; and
a vehicle speed measurement sensor that measures the speed of a wheel of the vehicle and generates vehicle speed data obtained by measuring a distance difference according to a location of the vehicle;
Energy harvesting power generation analyzer characterized in that it comprises a. According to claim 1,
The prediction unit,
The amount of power generation predicted based on the predicted amount of power generation is reflected as the required energy required for the entire preset section to calculate the energy use time and remaining energy amount of the entire section, and the operation is based on the energy use time and the remaining energy amount. Energy harvesting power generation analyzer, characterized in that for calculating the available time. According to claim 1,
The prediction unit,
An energy harvesting power generation analysis device, characterized in that for predicting the current battery charging amount by adding the power amount corresponding to the power generation prediction data to the current charging amount. According to claim 3,
The prediction unit,
Energy harvesting power generation analysis device, characterized in that for calculating the energy consumption pattern for each energy source after checking the power consumption for each energy source consumed in the current battery charge amount. delete According to claim 1,
The monitoring unit,
An energy harvesting power generation analysis device, characterized in that for outputting the amplitude of the vibration displacement data, the temperature data, and the vehicle speed measurement data in the form of a graph over time. According to claim 1,
The prediction unit,
A vibration energy harvesting power generation prediction model that converts acceleration, displacement, and frequency into numerical values based on the vibration displacement data and predicts power generation according to output based on the converted values;
a thermoelectric energy harvesting power generation prediction model that converts an exhaust port temperature and ambient air temperature into numerical values based on the temperature data and then predicts power generation according to output based on the converted values;
an eddy current energy harvesting power generation prediction model that converts distance differences according to acceleration, wheel speed, and vehicle position into numerical values based on the vehicle speed data, and predicts power generation according to output based on the converted values;
Energy harvesting power generation analyzer characterized in that it comprises a. According to claim 7,
The vibration energy harvesting power generation prediction model is
Analyzing the acceleration and amplitude of the suspension based on the vibration displacement data, matching with a vibration energy harvesting database based on the acceleration, the amplitude, and the load of the vibration displacement measurement sensor,
An energy harvesting power generation analysis device, characterized in that for calculating a vibration energy harvesting output by performing an operation based on the acceleration, the amplitude, and the vibration displacement measuring sensor matched with the vibration energy harvesting database. According to claim 8,
The vibration energy harvesting power generation prediction model is
A vibration energy harvesting value is calculated by multiplying the vibration energy harvesting output by time, a vibration energy battery charging value is calculated by adding an initial charging voltage to the vibration energy harvesting value, and a vibration sensor from the vibration energy battery charging value Energy harvesting power generation analysis device, characterized in that for calculating the current battery charge by subtracting the load power. According to claim 7,
The thermoelectric energy harvesting power generation prediction model is
Based on the temperature data, the exhaust temperature, the ambient air temperature, and the temperature difference (ΔT) are checked, the exhaust temperature, the ambient air temperature, and the temperature difference (ΔT) are matched with a thermoelectric energy harvesting database, and the thermoelectric energy Energy harvesting power generation analyzer, characterized in that for calculating the temperature energy harvesting output based on the temperature of the exhaust port, the ambient air temperature, and the temperature difference (ΔT) matched to the harvesting database. According to claim 10,
The thermoelectric energy harvesting power generation prediction model is
A temperature energy harvesting value is calculated by multiplying the temperature energy harvesting output by time, a temperature energy battery charging value is calculated by adding an initial charging voltage to the temperature energy harvesting value, and the temperature energy battery charging value is used as the temperature sensor Energy harvesting power generation analysis device, characterized in that for calculating the current battery charge by subtracting the load power. According to claim 7,
The eddy current energy harvesting power generation prediction model,
Checking wheel rotational speed based on the measured vehicle speed and wheel size, matching with the Eddy Current energy harvesting database based on the wheel rotational speed, and matching the Eddy Current energy harvesting database Energy harvesting power generation analyzer, characterized in that for calculating the vehicle speed energy harvesting output based on the wheel rotation speed and eddy current. According to claim 12,
The eddy current energy harvesting power generation prediction model,
A vehicle speed energy harvesting value is calculated by multiplying the vehicle speed energy harvesting output by time, a vehicle speed energy battery charging value is calculated by adding an initial charging voltage to the vehicle speed energy harvesting value, and the vehicle speed energy battery charging value is used as the vehicle speed sensor. Energy harvesting power generation analysis device, characterized in that for calculating the current battery charge by subtracting the load power.

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