New energy automobile energy recovery cable health monitoring device, method and equipment

Abstract

The invention discloses a new energy vehicle energy recovery cable health monitoring device, method and equipment, and belongs to the technical field of vehicle cables. The device comprises a motion data acquisition module used for acquiring motion data of the new energy automobile in the energy recovery process of the new energy automobile; the electrical data acquisition module is used for acquiring electrical data of the energy recovery cable in the energy recovery process; the data analysis module is used for constructing the motion data and the electrical data into a data pair and inputting the data pair into a health state analysis model; and the prompt module is used for determining the health state of the energy recovery cable according to the output result, and generating prompt information when the health state is sub-health or a fault exists. According to the technical scheme, whether the energy recovery cable of the new energy automobile is in the healthy state or not can be determined, guarantee is provided for energy recovery of the new energy automobile, it is ensured that the endurance mileage of the new energy automobile is not affected, and the driving experience of a user is improved.

Description

Technical Field

[0001] This application belongs to the technical field of vehicle cables, and specifically relates to a health monitoring device, method, and equipment for energy recovery cables of new energy vehicles. Background Art

[0002] With the rapid development of technology, new energy vehicles have gradually gained wide popularity among users. In new energy vehicles, an important function is energy recovery, that is, during the vehicle operation deceleration phase, the generated electric energy is recovered to the electric energy storage device to improve the vehicle's endurance.

[0003] Currently, during the electric energy recovery process, the recovered electric energy is transmitted to the electric energy storage device through cables. However, since energy recovery is a frequently occurring process, the cables need to frequently cope with rapid changes in current and charge-discharge cycles, and the frequency is much higher than that of ordinary vehicle cables. This requires that the conductive materials, insulating materials, etc. of the energy recovery cables can still maintain stable electrical performance in a high-frequency charge-discharge environment, otherwise problems such as power loss, signal interference, and accelerated insulation aging caused by repeated electromagnetic induction, capacitance effects, etc. will occur. Therefore, how to effectively monitor the health of energy recovery cables has become a technical issue of concern. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide a health monitoring device, method, and equipment for energy recovery cables of new energy vehicles, aiming to determine whether the energy recovery cables of new energy vehicles are in a healthy state by collecting motion data and electrical data and combining and analyzing the two, providing guarantee for the energy recovery of new energy vehicles, ensuring that the endurance of new energy vehicles is not affected, and improving the user's driving experience.

[0005] In a first aspect, the embodiments of this application provide a health monitoring device for energy recovery cables of new energy vehicles, and the device includes:

[0006] A motion data acquisition module, configured to acquire motion data of a new energy vehicle during the energy recovery process of the new energy vehicle;

[0007] An electrical data acquisition module, configured to collect electrical data of the energy recovery cable during the energy recovery process; wherein, the electrical data includes voltage data and current data, and the current data includes one or more of current magnitude, current stability, and harmonic components;

[0008] A data analysis module, configured to construct the motion data and the electrical data into a data pair and input it into a pre-generated health status analysis model;

[0009] A prompt module, configured to determine the health status of the energy recovery cable according to the output result of the health status analysis model, and generate a prompt message when the health status is sub-healthy or a fault exists.

[0010] Further, the data analysis module includes:

[0011] A normalization processing unit, configured to perform normalization processing on the motion data and the electrical data respectively;

[0012] A data pair construction unit, configured to construct data pairs from the data obtained after normalization processing;

[0013] A data input unit, configured to input the constructed data pairs into a pre-generated health status analysis model.

[0014] Further, the data analysis module further includes:

[0015] A weight assignment unit, configured to assign weights to each data in the data pair to obtain the weight value of each data;

[0016] Correspondingly, the data input unit is specifically configured to input the constructed data pairs together with the weight value of each data in the data pair into a pre-generated health status analysis model.

[0017] Further, the device further includes:

[0018] A mileage information acquisition module, configured to acquire the mileage information of the new energy vehicle;

[0019] Correspondingly, the data analysis module further includes:

[0020] A weight adjustment unit, configured to adjust the weights of each data in the data pair according to the mileage information to obtain the weight adjustment value of each data.

[0021] Further, the motion data includes the running speed, acceleration, steering angle and body inclination of the new energy vehicle.

[0022] Further, the data analysis module is further configured to:

[0023] Perform spectrum analysis on the current data by using fast Fourier transform, identify the amplitude information and phase information of each harmonic of the energy recovery cable, and determine whether there is harmonic abnormality in the energy recovery cable according to the amplitude information and the phase information.

[0024] Further, the prompt module is further configured to:

[0025] When there is an abnormal harmonic in the energy recovery cable, a prompt message for adding a harmonic suppression device is generated to add a counteracting harmonic current with the opposite phase in the energy recovery cable.

[0026] In a second aspect, an embodiment of the present application provides a method for health monitoring of an energy recovery cable of a new energy vehicle. The method includes:

[0027] During the energy recovery process of the new energy vehicle, obtain the motion data of the new energy vehicle;

[0028] Collect the electrical data of the energy recovery cable during the energy recovery process; wherein, the electrical data includes voltage data and current data, and the current data includes one or more of current magnitude, current stability, and harmonic components;

[0029] Construct a data pair from the motion data and the electrical data and input it into a pre-generated health status analysis model;

[0030] According to the output result of the health status analysis model, determine the health status of the energy recovery cable, and generate a prompt message when the health status is sub-healthy or there is a fault.

[0031] Further, constructing a data pair from the motion data and the electrical data and inputting it into a pre-generated health status analysis model includes:

[0032] Perform normalization processing on the motion data and the electrical data respectively;

[0033] Construct a data pair from the data obtained after the normalization processing;

[0034] Input the constructed data pair into a pre-generated health status analysis model.

[0035] In a third aspect, an embodiment of the present application provides an electronic device. The electronic device includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.

[0036] In a fourth aspect, an embodiment of the present application provides a readable storage medium. A program or instruction is stored on the readable storage medium. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0037] In a fifth aspect, an embodiment of the present application provides a chip. The chip includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0038] In an embodiment of the present application, a motion data acquisition module is configured to acquire motion data of a new energy vehicle during the energy recovery process of the new energy vehicle; an electrical property data acquisition module is configured to acquire electrical property data of an energy recovery cable during the energy recovery process; wherein, the electrical property data includes voltage data and current data, and the current data includes one or more of current magnitude, current stability, and harmonic components; a data analysis module is configured to construct the motion data and the electrical property data into a data pair and input the data pair into a pre-generated health status analysis model; a prompt module is configured to determine the health status of the energy recovery cable according to the output result of the health status analysis model, and generate a prompt information when the health status is sub-healthy or a fault exists. The above technical solution can collect motion data and electrical property data, and combine and analyze the two to determine whether the energy recovery cable of the new energy vehicle is in a healthy state, provide guarantee for the energy recovery of the new energy vehicle, ensure that the cruising range of the new energy vehicle is not affected, and improve the driving experience of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a schematic structural diagram of a health monitoring device for an energy recovery cable of a new energy vehicle provided in Embodiment 1 of the present application;

[0040] Figure 2 is a schematic structural diagram of a health monitoring device for an energy recovery cable of a new energy vehicle provided in Embodiment 2 of the present application;

[0041] Figure 3 is a schematic flowchart of a health monitoring method for an energy recovery cable of a new energy vehicle provided in Embodiment 3 of the present application;

[0042] Figure 4 is a schematic structural diagram of an electronic device provided in Embodiment 4 of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] To make the objectives, technical solutions, and advantages of this application more clear, the following further describes specific embodiments of this application in conjunction with the accompanying drawings. It can be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application. Additionally, it should be noted that for ease of description, only parts related to this application rather than all content are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of the operations can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. When the operations are completed, the process can be terminated, but there can also be additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0044] The following will clearly describe the technical solutions in the embodiments of this application in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some but not all of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application belong to the scope of protection of this application.

[0045] The terms "first", "second", etc. in the description and claims of this application are used to distinguish similar objects and are not used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are usually of the same type, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "and / or" in the description and claims means at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0046] The following, in conjunction with the accompanying drawings, through specific embodiments and their application scenarios, details the new energy vehicle energy recovery cable health monitoring device, method, and equipment provided by the embodiments of this application.

[0047] Embodiment 1

[0048] Figure 1 is a schematic structural diagram of the new energy vehicle energy recovery cable health monitoring device provided in Embodiment 1 of this application. As Figure 1 shown, the device includes:

[0049] A motion data acquisition module 110, configured to acquire motion data of the new energy vehicle during the energy recovery process of the new energy vehicle;

[0050] The electrical data acquisition module 120 is used to acquire the electrical data of the energy recovery cable during the energy recovery process. Among them, the electrical data includes voltage data and current data, and the current data includes one or more of current magnitude, current stability, and harmonic components.

[0051] The data analysis module 130 is used to construct the motion data and the electrical data into data pairs and input them into a pre-generated health status analysis model.

[0052] The prompt module 140 is used to determine the health status of the energy recovery cable according to the output result of the health status analysis model, and generate a prompt message when the health status is sub-healthy or there is a fault.

[0053] Among them, a new energy vehicle can be a vehicle that uses a new power system and is completely or mainly driven by new energy, such as a pure electric vehicle, a hybrid vehicle, etc. Here, it specifically refers to such a vehicle that is in the process of energy recovery, which has an energy recovery system and can convert part of the kinetic energy during vehicle braking or deceleration into electrical energy and store it.

[0054] Energy recovery is the process in which a new energy vehicle converts the mechanical energy of the vehicle into electrical energy and stores it in the battery through methods such as motor reverse during deceleration or braking. For example, using regenerative braking technology, when the vehicle brakes, the drive motor switches to the generator mode, converting the rotational energy of the wheels into electrical energy to achieve energy recovery and reuse.

[0055] The motion data can be various information describing the motion state of a new energy vehicle, which can include vehicle speed, obtained by a high-precision lidar speed measurement technology; acceleration, measured by an acceleration sensor with an adaptive filtering function, which can sense the changes in vehicle acceleration or deceleration in real time; vehicle attitude data, using a technology that combines an inertial measurement unit and a vision sensor, and accurately obtaining attitude information such as the pitch angle, roll angle, and yaw angle of the vehicle through the combination of image recognition and inertial measurement.

[0056] This solution can use specific sensors and data acquisition technologies to collect relevant motion data from the operating environment of a new energy vehicle.

[0057] The electrical data acquisition module 120 can acquire the electrical data of the energy recovery cable during the energy recovery process. Among them, the energy recovery cable can be a cable used to transmit the recovered electrical energy in the energy recovery system of a new energy vehicle. It needs to have good electrical conductivity and electromagnetic interference resistance, and may adopt a new superconducting material coating technology to reduce resistance loss, and at the same time adopt a multi-layer shielding structure to effectively resist external electromagnetic interference.

[0058] Specifically, the electrical data can include voltage data, i.e., the potential difference across the cable ends, which can be measured by a high-precision fiber optic voltage sensor and features anti-electromagnetic interference and high precision; current data, which is a set of parameters describing the current characteristics in the cable, covering aspects such as current magnitude, stability, and harmonic components. Among them, the voltage data can reflect the value of the potential difference across the cable ends and is crucial for evaluating the power transmission efficiency and stability of the energy recovery system. In the current data, the current magnitude can refer to the amount of charge passing through the cable cross-section per unit time, which is measured by a high-precision current sensor based on the Hall effect and can be accurate to the milliampere level. The current stability can reflect the degree of current fluctuation, and by performing real-time spectrum analysis and wavelet transform algorithm processing on the collected current signal, the stability of the current can be accurately evaluated. The harmonic components are the other frequency components in the current besides the fundamental wave component due to the action of non-linear loads such as power electronic devices. Using an artificial intelligence-based harmonic analysis algorithm, the amplitude, phase, and other information of each harmonic can be quickly and accurately identified and analyzed.

[0059] This solution can use specific sensors and measurement technologies to obtain various types of electrical data from the energy recovery cable. For example, high-speed synchronous acquisition technology is adopted to ensure that the voltage and current data are acquired under the same time reference, improving the accuracy and relevance of the data.

[0060] The data analysis module 130 can construct the motion data and the electrical data into data pairs and input them into a pre-generated health status analysis model. Among them, the data pair is a data set composed of motion data and electrical data combined according to certain rules and is used for subsequent input into the analysis model for correlation analysis. For example, the vehicle speed at the same moment and the corresponding current magnitude are combined into a data pair.

[0061] The health status analysis model can be obtained by training with a large amount of historical data and can evaluate the health status of the energy recovery cable based on the input motion data and electrical data. It may be constructed by combining the long short-term memory network LSTM in deep learning with transfer learning technology, using the model parameters that have been trained in other similar power system monitoring fields to speed up the training speed and improve the accuracy of the model's evaluation of the cable health status.

[0062] In this solution, the motion data and the electrical data can be combined according to a specific time or logical relationship to form data pairs. For example, through timestamp matching, different types of data collected at the same time point can be accurately combined. The constructed data pairs are transmitted to the health status analysis model for the model to perform calculations and analyses.

[0063] The prompt module 140 can be a functional unit that conveys the health status information of the energy recovery cable to the user. Among them, the health status can refer to the working state of the energy recovery cable, which is divided into different levels such as normal, sub-healthy, and faulty. It is judged based on the output result of the health status analysis model. For example, the probability value output by the model is compared with the set threshold to determine the health status level. When the cable is in a sub-healthy or faulty state, the prompt module generates information to inform the user of the relevant situation. It may include text prompts such as "The cable current harmonic is abnormal, it is recommended to check"; voice prompts, and the relevant information is played to the user in the form of voice through voice synthesis technology.

[0064] In this solution, the health status of the energy recovery cable can be judged according to the output result of the health status analysis model. For example, through the preset health status judgment rules, the characteristic values or probability values output by the model are analyzed to determine the cable health status. When the cable is in a sub-healthy or faulty state, corresponding prompt information is created. Using natural language generation technology, detailed and easy-to-understand prompt information is generated according to the specific abnormal situation of the cable.

[0065] The technical solution provided in this embodiment monitors the health of the energy recovery cable during operation under complex working conditions, discovers potential problems in advance, provides a strong guarantee for the stable and efficient operation of the energy recovery system of new energy vehicles, and reduces the vehicle performance degradation and safety risks caused by energy recovery cable failures.

[0066] Embodiment 2

[0067] On the basis of the above embodiment, this embodiment is further optimized. Specifically, the optimization is as follows: the data analysis module includes: a normalization processing unit for respectively performing normalization processing on the motion data and the electrical data; a data pair construction unit for constructing data pairs on the data obtained after normalization processing; and a data input unit for inputting the constructed data pairs into a pre-generated health status analysis model. Figure 2 It is a schematic structural diagram of the health monitoring device for the energy recovery cable of a new energy vehicle provided in Embodiment 2 of the present application. As Figure 2 shown, the device includes:

[0068] A motion data acquisition module 210, configured to acquire the motion data of a new energy vehicle during the energy recovery process of the new energy vehicle;

[0069] An electrical data acquisition module 220, configured to acquire the electrical data of the energy recovery cable during the energy recovery process; wherein, the electrical data includes voltage data and current data, and the current data includes one or more of the current magnitude, current stability, and harmonic components;

[0070] A data analysis module 230, configured to construct the motion data and the electrical data into data pairs and input them into a pre-generated health status analysis model;

[0071] A prompt module 240, configured to determine the health status of the energy recovery cable according to the output result of the health status analysis model, and generate a prompt message when the health status is sub-healthy or there is a fault;

[0072] Wherein, the data analysis module 230 includes:

[0073] A normalization processing unit 231, configured to perform normalization processing on the motion data and the electrical data respectively;

[0074] A data pair construction unit 232, configured to construct data pairs from the data obtained after normalization processing;

[0075] A data input unit 233, configured to input the constructed data pairs into a pre-generated health status analysis model.

[0076] Wherein, normalization can be to convert data with different ranges and scales into a unified standard range for easy data comparison, analysis, and model processing. In this solution, a dynamic normalization method based on machine learning prediction is innovatively adopted. Traditional normalization methods, such as min-max normalization and Z-score normalization, usually rely on fixed statistics such as minimum, maximum, mean, and standard deviation. In this solution, the distribution trend of the data is predicted through machine learning algorithms, and the normalization parameters are dynamically adjusted according to the prediction results, making the normalized data more conducive to subsequent analysis. For example, for the fluctuations in current data during the energy recovery process, dynamic normalization can adjust the normalization range in real time according to the predicted current change trend.

[0077] In this solution, for these two different types of data, namely motion data and electrical data, specific normalization algorithms can be used to independently convert them into a unified numerical range. For example, first, for each parameter in the motion data, such as vehicle speed and acceleration, according to its own data characteristics and predicted distribution, a dynamic normalization algorithm is used for processing; then, for parameters such as voltage, current magnitude, current stability, and harmonic components in the electrical data, dynamic normalization operations are performed according to their respective characteristics. Through this separate processing method, it is ensured that each type of data can retain its original characteristics after normalization and can be analyzed on the same scale as the other type of data.

[0078] A data pair can be a binary data structure formed by combining normalized motion data and electrical data according to a specific relationship. This combination is not random but based on the physical and logical relationships between the data. For example, a data pair may contain the normalized vehicle speed at a specific moment and the magnitude of the normalized current corresponding to that moment, which together reflect the correlation between the vehicle motion state and the electrical performance of the energy recovery cable at that instant.

[0079] In this solution, for the construction of data pairs, the normalized motion data and electrical data can be matched and combined into data pairs according to pre-set rules. These rules are not only based on time synchronization but also consider the physical meaning and correlation of the data. For example, by establishing a correlation model based on vehicle dynamics and circuit principles, this model can analyze the electrical performance response of the energy recovery system under different motion states, thereby determining which motion data and electrical data should be combined together. Then, according to this model, the qualified normalized data are combined into data pairs one by one to provide a structured data sample for subsequent analysis. This solution can transmit the data pairs generated by the data pair construction unit to the model in the format and order required by the health state analysis model as the input data for the model to perform calculations and analysis.

[0080] This technical solution can provide a high-quality data processing flow for the health state analysis of energy recovery cables through innovative normalization methods, intelligent data pair construction strategies, and data input methods adapted to advanced models. Dynamic normalization makes different types of data more comparable, data pairs constructed based on physical and logical relationships can better reflect the internal connection between the vehicle and the cable, and data input adapted to complex models ensures that advanced models can give full play to their advantages. This solution improves the accuracy of the health state assessment of energy recovery cables, helps to detect potential problems in a timely manner, and ensures the stable operation of the energy recovery system of new energy vehicles.

[0081] In one embodiment, optionally, the data analysis module further includes:

[0082] A weight assignment unit for assigning weights to each data in the data pair to obtain the weight value of each data;

[0083] Correspondingly, the data input unit is specifically configured to input the constructed data pair together with the weight value of each data in the data pair into a pre-generated health state analysis model.

[0084] Among them, the weight value is the specific quantitative value of the weight, usually taking values between 0 and 1, and the sum of the weight values of all data is 1. Different data are assigned different weight values according to their roles in the health state analysis.

[0085] In this solution, specific algorithms and rules can be used to determine the weight value for each data in the data pair based on various factors such as the characteristics of the data, the degree of influence on the cable health status, and the actual operating conditions. For example, a feature importance evaluation algorithm based on machine learning can be adopted to determine the importance of each data in judging the cable health status through learning and analysis of a large amount of historical data, and then allocate the corresponding weight value. Professional knowledge and real-time monitored working condition information can also be combined to dynamically adjust the weight allocation strategy.

[0086] This solution can integrate the constructed data pairs and the weight values corresponding to each data, and transmit them to the model together in a format that the health status analysis model can recognize and process. For example, represent the data pair in vector form, and at the same time represent the corresponding weight value in another vector form, and then combine these two vectors into a new input vector and input it into the health status analysis model. This can enable the model to fully consider the importance of each data during analysis and improve the accuracy of the analysis results.

[0087] This technical solution can fully consider various factors, reasonably allocate weights for each data in the data pair, and highlight the role of the data that is more critical for judging the cable health status. This solution can significantly improve the accuracy of the output results of the health status analysis model, can more accurately evaluate the health status of the energy recovery cable, timely discover potential problems, and provide more powerful guarantee for the stable operation of the new energy vehicle energy recovery system.

[0088] In one embodiment, optionally, the device further includes:

[0089] A mileage information acquisition module, configured to acquire the mileage information of the new energy vehicle;

[0090] Correspondingly, the data analysis module further includes:

[0091] A weight adjustment unit, configured to adjust the weights of the data in the data pair according to the mileage information to obtain the weight adjustment value of each data.

[0092] Among them, the mileage information can be the total distance traveled by the new energy vehicle from the factory to the current moment. The mileage information is an important indicator reflecting the usage degree and wear condition of the vehicle, and is of great significance for evaluating the health status of the energy recovery cable. Different driving mileages may correspond to different cable aging degrees and working environments, thereby affecting the importance of each data for evaluating the cable health status.

[0093] This solution can collect mileage data from relevant vehicle systems through specific hardware devices and data acquisition technologies. Taking high-precision satellite positioning technology as an example, this module will receive satellite signals in real time, calculate the driving mileage by analyzing the position information in the signals and combining the vehicle's driving trajectory. At the same time, it compares and fuses with the odometer sensor data inside the vehicle to finally obtain accurate and reliable mileage information.

[0094] The weight adjustment unit can dynamically adjust the weights of the data in the data pair according to the obtained mileage information. It uses intelligent algorithms and preset rules, comprehensively considering the relationship between mileage and the cable health status, to achieve more accurate weight allocation. For example, a regression model based on machine learning is adopted to analyze the influence changes of each data on the cable health status judgment at different mileage stages, so as to adjust the weights. The new weight value obtained after the weight adjustment unit adjusts according to the mileage information on the basis of the original weight value.

[0095] This solution can modify the original weight values of the data in the data pair according to the mileage information, combined with preset algorithms and rules. Specifically, the weight adjustment unit will set different weight adjustment coefficients for each data according to different mileage intervals. For example, when the vehicle's driving mileage is short, the influence of current stability data on the cable health status may be greater; as the driving mileage increases, the insulation performance of the cable may gradually decline, and at this time the weight of voltage data may need to be increased accordingly. The weight adjustment unit will calculate the weight adjustment value of each data according to these changes, making the subsequent health status analysis more in line with the actual situation of the vehicle.

[0096] This technical solution accurately obtains the mileage information of new energy vehicles and dynamically adjusts the weights of the data in the data pair according to the mileage information, enabling the health status analysis model to fully consider the vehicle's usage degree and the cable's aging situation. This weight adjustment mechanism combined with mileage information improves the accuracy and pertinence of health status analysis, can more accurately detect potential problems that may occur in the energy recovery cable at different usage stages, and provides more effective guarantee for the stable operation of the new energy vehicle energy recovery system.

[0097] In the above embodiments, optionally, the motion data includes the running speed, acceleration, steering angle and body tilt of the new energy vehicle.

[0098] The running speed can refer to the distance traveled by a new energy vehicle per unit time during driving, which is a physical quantity describing the speed of vehicle movement. Its measurement can be carried out in various ways. Traditionally, the wheel speed sensor is used to measure the wheel rotation speed, and then the vehicle speed is calculated in combination with the wheel radius. The acceleration can include the acceleration during acceleration and deceleration. It is usually measured using an acceleration sensor. General acceleration sensors are based on microelectromechanical system (MEMS) technology. The steering angle can refer to the angle by which the steering wheel or wheels rotate when the vehicle steers, reflecting the change in the driving direction of the vehicle. A steering angle sensor can be used to measure the steering angle. Common ones are potentiometer-type and Hall-type sensors. The body tilt can represent the degree of tilt of the vehicle body relative to the horizontal plane, usually measured by a tilt sensor installed on the vehicle. Traditional tilt sensors may have problems such as low accuracy and slow response speed. This solution can measure the body tilt by fusing an Inertial Measurement Unit (IMU) and a barometric sensor. The IMU can measure the acceleration and angular velocity of the vehicle in real time, and obtain the attitude information of the vehicle through integral operation. The barometric sensor can assist in judging the height change of the vehicle, and further correct the measurement result of the tilt. The body tilt will affect the center of gravity distribution of the vehicle and the friction between the tires and the ground. During the energy recovery process, it is necessary to consider the impact of the body tilt on the braking effect and energy conversion.

[0099] This solution helps to more comprehensively and meticulously describe the movement state of a new energy vehicle during the energy recovery process by clarifying that the movement data includes running speed, acceleration, steering angle, and body tilt. This solution can improve the efficiency and effect of energy recovery, and also helps to ensure the driving stability and safety of the vehicle during the energy recovery process.

[0100] In the above embodiments, optionally, the data analysis module is further configured to:

[0101] Perform spectral analysis on the current data using the fast Fourier transform to identify the amplitude information and phase information of each harmonic of the energy recovery cable, and determine whether there is a harmonic anomaly in the energy recovery cable according to the amplitude information and the phase information.

[0102] In this solution, the fast Fourier transform (FFT) is an efficient algorithm for calculating the discrete Fourier transform (DFT). The DFT can convert a time-domain signal into a frequency-domain signal to analyze the frequency components of the signal. The FFT greatly reduces the amount of calculation and improves the calculation speed through a clever algorithm structure. In this solution, it is used to process the current data to extract the different frequency components contained therein. This solution can adopt an improved adaptive FFT algorithm to automatically adjust the calculation parameters according to the characteristics of the current data, further improving the calculation efficiency and accuracy.

[0103] Spectrum analysis can be to convert a signal from the time domain to the frequency domain for analysis. By performing spectrum analysis on the signal, the distribution of different frequency components in the signal can be understood. In the current data of the energy recovery cable, spectrum analysis can help us identify the harmonic components contained therein.

[0104] Harmonics can refer to sinusoidal wave components with frequencies that are integer multiples of the fundamental frequency. In a power system, the fundamental frequency is usually 50Hz or 60Hz, and the frequencies of harmonics are 2 times, 3 times, etc. of the fundamental frequency. In the energy recovery cable, the presence of harmonics may cause problems such as cable heating, increased power loss, and electromagnetic interference. Each harmonic corresponds to a different frequency multiple. For example, the frequency of the second harmonic is 2 times the fundamental frequency, and the frequency of the third harmonic is 3 times the fundamental frequency, and so on.

[0105] Amplitude information can be the amplitude sizes of each harmonic. In spectrum analysis, amplitude information reflects the intensity of each harmonic component in the signal. For example, harmonics with larger amplitudes may have a more significant impact on the cable and may cause more serious heating and power loss problems. By accurately obtaining amplitude information, the impact degree of each harmonic on the energy recovery cable can be evaluated. Phase information describes the time offset of each harmonic relative to the fundamental wave. Harmonics with different phases will produce different effects when superimposed. For example, the superposition of harmonics with certain phases may cause the current in the cable to increase instantaneously, thus increasing the burden on the cable. Phase information is very important for comprehensively understanding the characteristics of harmonics and their interactions.

[0106] Harmonic anomalies can be situations where the harmonic components in the energy recovery cable do not meet the normal operation standards. This may be manifested as excessive amplitudes of certain harmonics, abnormal phases, etc. Harmonic anomalies may affect the normal operation of the cable, resulting in problems such as cable heating, accelerated insulation aging, and degraded power quality, and may even affect the stability and safety of the energy recovery system of new energy vehicles.

[0107] This solution uses the Fast Fourier Transform (FFT) for spectrum analysis. It means taking the collected current data as input and applying the FFT algorithm to transform it from the time domain to the frequency domain to obtain the spectrum of the current signal. In actual operation, first, the current data is preprocessed, such as filtering to remove noise interference, and then the processed data is input into the improved adaptive FFT algorithm for calculation. Through spectrum analysis, the distribution of each frequency component in the current signal can be obtained, and then each harmonic can be identified. In the results obtained from spectrum analysis, the amplitude information and phase information of each harmonic are accurately found. This requires analyzing and processing the spectrogram, determining the position of each harmonic according to the characteristics of the harmonic frequency, and reading its corresponding amplitude and phase values. This solution can use an automated algorithm to achieve harmonic identification, improving the accuracy and efficiency of identification. Furthermore, based on the identified amplitude information and phase information, it is judged whether there is a harmonic anomaly in the energy recovery cable. This requires presetting the amplitude and phase ranges of each harmonic under normal operating conditions. Comparing the actually measured amplitude and phase information with the standard range, if the amplitude or phase of some harmonics exceeds the standard range, it is determined that there is a harmonic anomaly in the cable. This solution can also use machine learning algorithms to learn a large amount of normal and abnormal data to establish a more accurate harmonic anomaly judgment model.

[0108] In this technical solution, by using the Fast Fourier Transform to perform spectrum analysis on the current data, the amplitude information and phase information of each harmonic in the energy recovery cable can be accurately identified. Based on this information, it is possible to determine in a timely and accurate manner whether there is a harmonic anomaly in the cable. This method can detect potential problems in the cable operation in advance, such as heat generation and increased power loss caused by harmonics, which helps to take corresponding measures for treatment, such as adjusting the control strategy of the energy recovery system, installing harmonic filters, etc., thereby improving the operation stability of the energy recovery cable, ensuring the normal operation of the new energy vehicle energy recovery system, extending the service life of the cable, and also helping to improve the power quality and reduce the electromagnetic interference to surrounding electronic devices.

[0109] In the above embodiments, optionally, the prompt module is further configured to:

[0110] In the case that there is a harmonic anomaly in the energy recovery cable, generate a prompt message to add a harmonic suppression device to add a counteracting harmonic current with the opposite phase in the energy recovery cable.

[0111] Among them, the harmonic suppression device can be a device used to reduce or eliminate harmonics in the power system. Its working principle is usually to generate a current with the same magnitude and opposite phase as the harmonic current, so as to cancel out the original harmonic current, make the current waveform closer to a sine wave, and improve the power quality. Common harmonic suppression devices include active power filters and passive filters, etc. In this solution, the adopted harmonic suppression device may incorporate advanced intelligent control technology, which can monitor the harmonic situation in real time and automatically adjust the output cancellation current.

[0112] Canceling the harmonic current means generating a current with the same magnitude and opposite phase as the original harmonic current in the cable through the harmonic suppression device. When these two currents are superimposed, they will cancel each other out, thereby reducing or eliminating the harmonic components in the cable.

[0113] In this solution, by installing a harmonic suppression device, specifically selecting a suitable harmonic suppression device according to the cable parameters and harmonic situation, planning the installation location and wiring, and debugging and calibrating the device, it is ensured that it can work properly and effectively cancel the harmonic current. During the installation process, an intelligent installation assistance system can be utilized to optimize the installation location and parameter settings through sensors and data analysis technology, improving the effect of harmonic suppression.

[0114] In this technical solution, when a harmonic anomaly is detected in the energy recovery cable, a prompt message for adding a harmonic suppression device is generated in a timely manner, enabling relevant personnel to quickly understand the abnormal situation of the cable and the method to solve the problem. By adding a harmonic suppression device to generate a cancellation harmonic current with the opposite phase, the harmonic components in the cable can be effectively reduced. This helps to reduce the heating and power loss of the cable, improve the service life of the cable and the efficiency of the energy recovery system.

[0115] Embodiment III

[0116] Figure 3 is a schematic flow chart of the method for monitoring the health of the energy recovery cable of a new energy vehicle provided by Embodiment III of this application. As Figure 3 shown, it specifically includes the following steps:

[0117] S301. During the energy recovery process of the new energy vehicle, obtain the motion data of the new energy vehicle;

[0118] S302. Collect the electrical data of the energy recovery cable during the energy recovery process; among them, the electrical data includes voltage data and current data, and the current data includes one or more of the current magnitude, current stability, and harmonic components;

[0119] S303. Construct the motion data and the electrical data into a data pair and input it into the pre-generated health status analysis model;

[0120] S304. Determine the health status of the energy recovery cable according to the output result of the health status analysis model, and generate a prompt message when the health status is sub-healthy or a fault exists.

[0121] Further, constructing the motion data and the electrical data into data pairs and inputting them into a pre-generated health status analysis model includes:

[0122] Perform normalization processing on the motion data and the electrical data respectively;

[0123] Construct data pairs for the data obtained after normalization processing;

[0124] Input the constructed data pairs into a pre-generated health status analysis model.

[0125] The technical solution provided in this embodiment, during the energy recovery process of a new energy vehicle, obtains the motion data of the new energy vehicle; collects the electrical data of the energy recovery cable during the energy recovery process; wherein, the electrical data includes voltage data and current data, and the current data includes one or more of current magnitude, current stability, and harmonic components; constructs the motion data and the electrical data into data pairs and inputs them into a pre-generated health status analysis model; determines the health status of the energy recovery cable according to the output result of the health status analysis model, and generates a prompt message when the health status is sub-healthy or a fault exists. This solution can collect motion data and electrical data, and combine and analyze the two to determine whether the energy recovery cable of the new energy vehicle is in a healthy state, provide guarantee for the energy recovery of the new energy vehicle, ensure that the cruising range of the new energy vehicle is not affected, and improve the driving experience of users.

[0126] The method for monitoring the health of the energy recovery cable of a new energy vehicle provided in the embodiments of this application corresponds to the device for monitoring the health of the energy recovery cable of a new energy vehicle provided in the above embodiments, has the same execution process and beneficial effects, and for the sake of avoiding repetition, will not be elaborated here.

[0127] Embodiment 4

[0128] As Figure 4 shown, an electronic device 400 is further provided in the embodiments of this application, including a processor 401, a memory 402, a program or instruction stored on the memory 402 and executable on the processor 401. When the program or instruction is executed by the processor 401, it realizes each process of the above embodiment of the device for monitoring the health of the energy recovery cable of a new energy vehicle, and can achieve the same technical effects. For the sake of avoiding repetition, will not be elaborated here.

[0129] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0130] Embodiment Five

[0131] The embodiments of the present application further provide a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements each process of the above-mentioned embodiment of the new energy vehicle energy recovery cable health monitoring device and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0132] Among them, the processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk or optical disc, etc.

[0133] Embodiment Six

[0134] The embodiments of the present application further provide a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run a program or instruction to implement each process of the above-mentioned embodiment of the new energy vehicle energy recovery cable health monitoring device and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0135] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip.

[0136] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the methods and devices in the embodiments of the present application are not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described method may be executed in an order different from that described, and various steps may be added, omitted or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0137] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present application.

[0138] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them belong to the protection scope of the present application.

[0139] The above is only the preferred embodiment of the present application and the technical principles applied. The present application is not limited to the specific embodiments described herein. Various obvious changes, re-adjustments, and substitutions that can be made by those skilled in the art will not depart from the protection scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments. Without departing from the concept of the present application, it can also include more other equivalent embodiments, and the scope of the present application is determined by the scope of the claims.

Claims

1. A health monitoring device for an energy recovery cable of a new energy vehicle, characterized in that, The device includes: A motion data acquisition module, configured to acquire the motion data of a new energy vehicle during the energy recovery process of the new energy vehicle; An electrical property data acquisition module, configured to acquire the electrical property data of the energy recovery cable during the energy recovery process; wherein, the electrical property data includes voltage data and current data, and the current data includes one or more of current magnitude, current stability, and harmonic components; A data analysis module, configured to construct the motion data and the electrical property data into a data pair and input it into a pre-generated health status analysis model; A prompt module, configured to determine the health status of the energy recovery cable according to the output result of the health status analysis model, and generate a prompt message when the health status is sub-healthy or a fault exists.

2. The new energy vehicle energy recovery cable health monitoring device according to claim 1, characterized in that, The data analysis module includes: A normalization processing unit, configured to perform normalization processing on the motion data and the electrical property data respectively; A data pair construction unit, configured to construct a data pair for the data obtained after the normalization processing; A data input unit, configured to input the constructed data pair into a pre-generated health status analysis model.

3. The new energy vehicle energy recovery cable health monitoring device according to claim 1, wherein The data analysis module further includes: A weight assignment unit, configured to assign weights to each data in the data pair to obtain a weight value for each data; Correspondingly, the data input unit is specifically configured to input the constructed data pair together with the weight value of each data in the data pair into a pre-generated health status analysis model.

4. The new energy vehicle energy recovery cable health monitoring device according to claim 3, characterized in that, The device further includes: A mileage information acquisition module, configured to acquire the mileage information of the new energy vehicle; Correspondingly, the data analysis module further includes: A weight adjustment unit, configured to adjust the weights of each data in the data pair according to the mileage information to obtain a weight adjustment value for each data.

5. The new energy vehicle energy recovery cable health monitoring device according to claim 1, characterized in that, The motion data includes the running speed, acceleration, steering angle, and body tilt of the new energy vehicle.

6. The health monitoring device for the energy recovery cable of a new energy vehicle according to claim 1, wherein, The data analysis module is further configured to: Perform spectral analysis on the current data by using fast Fourier transform, identify the amplitude information and phase information of each harmonic of the energy recovery cable, and determine whether there is harmonic abnormality in the energy recovery cable according to the amplitude information and the phase information.

7. The new energy vehicle energy recovery cable health monitoring device according to claim 6, characterized in that, The prompt module is further configured to: Generate a prompt message for adding a harmonic suppression device when there is harmonic abnormality in the energy recovery cable, so as to add a canceling harmonic current with opposite phase in the energy recovery cable.

8. A method for health monitoring of an energy recovery cable of a new energy vehicle, characterized in that, The method includes: Acquiring the motion data of a new energy vehicle during the energy recovery process of the new energy vehicle; Collecting the electrical property data of the energy recovery cable during the energy recovery process; wherein, the electrical property data includes voltage data and current data, and the current data includes one or more of current magnitude, current stability, and harmonic components; Constructing the motion data and the electrical property data into a data pair and inputting it into a pre-generated health status analysis model; Determining the health status of the energy recovery cable according to the output result of the health status analysis model, and generating a prompt message when the health status is sub-healthy or a fault exists.

9. The method for health monitoring of the energy recovery cable of a new energy vehicle according to claim 8, wherein, Constructing the motion data and the electrical data into data pairs and inputting them into a pre-generated health status analysis model includes: Performing normalization processing on the motion data and the electrical data respectively; Constructing data pairs for the data obtained after the normalization processing; Inputting the constructed data pairs into a pre-generated health status analysis model.

10. An electronic device, characterized in that, It includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the new energy vehicle energy recovery cable health monitoring method described in any one of claims 8-9 are implemented.

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