Self-assisting system and control method thereof

Abstract

The invention relates to the technical field of unmanned vehicle power assisting systems, and provides a self-power assisting system and a control method thereof.The system comprises a sensing data obtaining terminal, a power assisting analysis terminal, a suspension adjusting terminal, a power adjusting terminal and an adjusting execution terminal; the sensing data acquisition terminal is used for acquiring suspension sensing data, vehicle condition sensing data and environment sensing data of the unmanned vehicle; the power-assisted analysis terminal is used for performing power-assisted behavior analysis according to the suspension sensing data, the environment sensing data and the vehicle condition sensing data to generate power-assisted analysis information; the suspension adjustment terminal is used for carrying out unmanned vehicle suspension adjustment strategy analysis according to the assistance analysis information and generating suspension adjustment strategy information; the power adjustment terminal is used for performing unmanned vehicle power adjustment strategy analysis according to the power-assisted analysis information to generate power adjustment strategy information; and the adjustment execution terminal is used for executing an adjustment strategy in the suspension adjustment strategy information and the power adjustment strategy information. The method has the effect of improving the driving stability of the unmanned vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned vehicle power-assisting systems, and in particular to a self-power-assisting system and a control method thereof. Background Art

[0002] With the rapid development of unmanned driving technology, unmanned vehicles have gradually entered people's lives. However, existing unmanned driving systems usually only focus on the vehicle's automatic navigation, obstacle avoidance and driving control, and fail to fully consider the vehicle's energy efficiency under complex road conditions. In various complex environments, such as roads with different slopes, different load conditions, and even bad weather, the vehicle's driving performance is often affected. Therefore, how to improve the adaptability of unmanned vehicles under various working conditions, especially how to optimize power output by intelligently adjusting the vehicle's power assist system, has become an important topic of current research.

[0003] Now many unmanned vehicle systems have been developed. After a lot of searching and reference, we found that the unmanned vehicle systems in the prior art include the unmanned vehicle systems disclosed in publication numbers CN115107730A, CN109552216A, CN101807079A, EP2655185A1, and US20200363823A1. These unmanned vehicle systems generally include: a sensor terminal, a power terminal, an unmanned vehicle body, and a control terminal; the sensor terminal is used to obtain the working sensor data of the unmanned vehicle body and the power terminal; the power terminal is used to provide power for the unmanned vehicle body; the control terminal is used to control the coordinated operation of the unmanned vehicle body, the sensor terminal, and the power terminal according to the working sensor data. Since the working mode of the above-mentioned unmanned vehicle system is relatively single, and there is a lack of power analysis process and suspension adjustment process, the unmanned vehicle has the defect of reduced driving stability. Summary of the invention

[0004] The purpose of the present invention is to provide a self-assisting system and a control method thereof in view of the deficiencies of the above-mentioned unmanned vehicle system.

[0005] The present invention adopts the following technical solution:

[0006] A self-assisted power system, comprising a sensor data acquisition terminal, a power analysis terminal, a suspension adjustment terminal, a power adjustment terminal and an adjustment execution terminal; the sensor data acquisition terminal is used to acquire suspension sensor data, vehicle condition sensor data and environment sensor data of an unmanned vehicle; the power analysis terminal is used to perform power assistance behavior analysis based on the suspension sensor data, environment sensor data and vehicle condition sensor data, and generate power assistance analysis information; the suspension adjustment terminal is used to perform suspension adjustment strategy analysis of the unmanned vehicle based on the power analysis information, and generate suspension adjustment strategy information; the power adjustment terminal is used to perform power adjustment strategy analysis of the unmanned vehicle based on the power analysis information, and generate power adjustment strategy information; the adjustment execution terminal is used to execute adjustment strategies in the suspension adjustment strategy information and the power adjustment strategy information;

[0007] The sensor data acquisition terminal includes a suspension sensor module, a vehicle condition sensor module and an environment sensor module; the suspension sensor module is used to collect suspension sensor data of the unmanned vehicle suspension system in real time; the vehicle condition sensor module is used to obtain real-time vehicle condition sensor data of the unmanned vehicle; the environment sensor module is used to obtain environmental sensor data of the external environment.

[0008] Optionally, the power assistance analysis terminal includes a data preprocessing module, a behavior recognition module and a power assistance analysis module; the data preprocessing module is used to preprocess the sensor data from the suspension sensor module, the vehicle condition sensor module and the environmental sensor module to eliminate noise and redundant information; the behavior recognition module is used to identify the current driving behavior pattern of the unmanned vehicle and changes in the driving environment based on the preprocessed sensor data; the power assistance analysis module is used to perform power assistance behavior analysis based on the driving behavior pattern, changes in the driving environment and sensor data to generate power assistance analysis information.

[0009] Optionally, the suspension adjustment terminal includes a suspension adjustment strategy analysis module, a suspension instruction generation module and a suspension adjustment strategy information generation module; the suspension adjustment strategy analysis module is used to perform suspension adjustment analysis based on power assistance analysis information; the suspension instruction generation module is used to generate suspension instructions based on the suspension adjustment analysis results; the suspension adjustment strategy information generation module is used to generate suspension adjustment strategy information based on the suspension instructions.

[0010] Optionally, the power adjustment terminal includes a power adjustment strategy analysis module, a power instruction generation module and a power adjustment strategy information generation module; the power adjustment strategy analysis module is used to perform power adjustment analysis based on the power assistance analysis information; the power instruction generation module is used to generate a power instruction based on the power adjustment analysis results; the power adjustment strategy information generation module is used to generate power adjustment strategy information based on the power instruction.

[0011] Optionally, the adjustment execution terminal includes a suspension execution module, a power execution module and a control feedback module; the suspension execution module is used to control the working parameters of the suspension system of the unmanned vehicle according to the suspension adjustment strategy information; the power execution module is used to adjust the power output of the power system of the unmanned vehicle according to the power adjustment strategy information; the control feedback module is used to monitor the execution effects of the suspension system and the power system in real time.

[0012] Optionally, the suspension adjustment strategy analysis module includes a suspension analysis parameter extraction submodule and a suspension stiffness adjustment index calculation submodule; the suspension analysis parameter extraction submodule is used to extract suspension analysis parameters according to the power assist analysis information; the suspension stiffness adjustment index calculation submodule is used to calculate the current suspension stiffness adjustment index of the unmanned vehicle according to the suspension analysis parameters.

[0013] Optionally, the power adjustment strategy analysis module includes a power analysis parameter extraction submodule and a power output adjustment index calculation submodule; the power analysis parameter extraction submodule is used to extract power analysis parameters based on power assistance analysis information; the power output adjustment index calculation submodule is used to calculate the current power output adjustment index of the unmanned vehicle based on the power analysis parameters.

[0014] A control method for a self-powered system is applied to a self-powered system as described above, and the control method for the self-powered system comprises:

[0015] S1, obtaining suspension sensor data, vehicle condition sensor data and environment sensor data of the unmanned vehicle;

[0016] S2, analyzing the power assist behavior according to the suspension sensor data, the environment sensor data and the vehicle condition sensor data, and generating power assist analysis information;

[0017] S3, performing suspension adjustment strategy analysis on the unmanned vehicle according to the power analysis information, and generating suspension adjustment strategy information;

[0018] S4, performing power adjustment strategy analysis on the unmanned vehicle according to the power analysis information, and generating power adjustment strategy information;

[0019] S5, executing the adjustment strategies in the suspension adjustment strategy information and the power adjustment strategy information.

[0020] The beneficial effects achieved by the present invention are:

[0021] 1. Through the setting of sensor data acquisition terminal, the suspension system, vehicle condition and environmental sensor data of unmanned vehicles are collected in real time, which can fully reflect the operating status of unmanned vehicles and changes in the external environment. This setting is conducive to the realization of all-round and multi-level real-time monitoring of unmanned vehicles, and then provides accurate data support for subsequent power analysis, suspension adjustment and power adjustment, which is conducive to improving the driving stability and intelligence level of unmanned vehicles.

[0022] 2. Through the setting of the power-assist analysis terminal, especially the collaborative work of the data preprocessing module, behavior recognition module and power-assist analysis module, it is possible to effectively remove noise and redundant information in the sensor data, accurately identify driving behavior patterns and environmental changes, and then generate power-assist analysis information based on these analysis results. This setting is conducive to achieving a dynamic understanding of the current driving state of the unmanned vehicle, and then provides a scientific basis for the vehicle's suspension and power adjustment strategy, thereby improving the system's response speed and adjustment accuracy, and improving the intelligent adjustment capabilities of the unmanned vehicle.

[0023] 3. Through the setting of the suspension adjustment terminal, combined with the coordinated work of the suspension adjustment strategy analysis module, the suspension command generation module and the suspension adjustment strategy information generation module, the suspension system of the unmanned vehicle can be efficiently analyzed and adjusted according to the power analysis information, and then accurate suspension adjustment strategy information can be generated. This setting is conducive to optimizing the performance of the suspension system in real time according to different road conditions and driving environments, thereby improving the stability and safety of the unmanned vehicle in various driving environments.

[0024] 4. Through the setting of the power adjustment terminal, especially the cooperation of the power adjustment strategy analysis module, the power command generation module and the power adjustment strategy information generation module, the vehicle's power system can be optimized and adjusted according to the power analysis information. This setting is conducive to automatically adjusting the power output according to different driving needs and road conditions, thereby providing the vehicle with a more stable and efficient power response, and ultimately improving the vehicle's acceleration performance, fuel efficiency and the adaptability of the overall power system.

[0025] 5. By adjusting the settings of the execution terminal, combined with the coordinated work of the suspension execution module, power execution module and control feedback module, the suspension and power adjustment strategies can be accurately executed, and the working status of the suspension system and power system can be monitored and adjusted in real time. This setting is conducive to ensuring that the adjustment of the suspension system and power system can be carried out according to the predetermined strategy, thereby maintaining the optimal performance of the unmanned vehicle during driving, avoiding instability caused by excessive adjustment, and improving the overall control accuracy of the vehicle.

[0026] 6. Through the setting of the suspension adjustment strategy analysis module, especially the coordinated work of the suspension analysis parameter extraction submodule and the suspension stiffness adjustment index calculation submodule, it is possible to accurately extract key suspension parameters and calculate the current suspension stiffness adjustment index, thereby optimizing the suspension stiffness adjustment strategy. This setting is conducive to dynamically adjusting the stiffness of the suspension system according to the real-time driving status and external road conditions, thereby effectively improving the driving stability of the vehicle, especially the adaptability under different road conditions.

[0027] 7. Through the setting of the power adjustment strategy analysis module, combined with the work of the power analysis parameter extraction submodule and the power output adjustment index calculation submodule, the current power output adjustment index can be accurately extracted and calculated based on the power analysis information, thereby providing a scientific basis for the adjustment of the power system. This setting is conducive to automatically adjusting the power output according to changes in the vehicle's load, speed, road conditions, etc., to achieve efficient energy management and power demand matching, thereby improving the performance of the vehicle's power system and enhancing its responsiveness and endurance under different driving conditions.

[0028] 8. The suspension selection algorithm can take into account changes in external wind speed, wind direction and wind force during the adjustment of the suspension system of unmanned vehicles. By incorporating these wind force factors into the suspension hardness adjustment formula, it is helpful to optimize the responsiveness of the suspension system and reduce the negative impact of wind force on the vehicle's driving stability. Furthermore, the suspension hardness can be adjusted in real time to adapt to the force exerted on the vehicle by changes in wind speed, thereby improving the driving stability of unmanned vehicles under complex weather conditions, especially in high wind speeds or unstable wind conditions, ensuring the rapid response of the vehicle's suspension system and the safety of the vehicle.

[0029] 9. Through the power output selection algorithm and the introduction of internal vibration factors, the impact of vibration frequencies and vibration amplitudes at different positions on the vehicle suspension system and power system can be considered. Incorporating vibration factors into the power output adjustment formula is conducive to real-time adjustment of the power output of the power system according to the vibration conditions of different parts of the vehicle, preventing the vehicle from being unbalanced or damaged due to excessive vibration. Furthermore, during dynamic driving, the power output is optimized according to vibration data, the driving stability of the vehicle is improved, and thus the control accuracy of the unmanned vehicle is improved, especially at high speeds or complex road conditions, which can better eliminate unnecessary vibration interference.

[0030] To further understand the features and technical contents of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are only for reference and description and are not intended to limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0032] Figure 2 It is a structural schematic diagram of the suspension adjustment strategy analysis module in the present invention;

[0033] Figure 3 It is a structural schematic diagram of the power adjustment strategy analysis module in the present invention;

[0034] Figure 4 The figure is a flow chart of a method for controlling a self-powered system in the present invention. DETAILED DESCRIPTION

[0035] The following is an explanation of the embodiments of the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are only simple schematic illustrations and are not depicted according to actual dimensions. It is stated in advance. The following embodiments will further explain the relevant technical contents of the present invention in detail, but the disclosed contents are not intended to limit the scope of protection of the present invention.

[0036] Embodiment 1: This embodiment provides a self-powered system. Figure 1 As shown, a self-assisted power system includes a sensor data acquisition terminal, a power analysis terminal, a suspension adjustment terminal, a power adjustment terminal and an adjustment execution terminal; the sensor data acquisition terminal is used to acquire suspension sensor data, vehicle condition sensor data and environment sensor data of an unmanned vehicle; the power analysis terminal is used to perform power assistance behavior analysis based on the suspension sensor data, environment sensor data and vehicle condition sensor data, and generate power assistance analysis information; the suspension adjustment terminal is used to perform suspension adjustment strategy analysis of the unmanned vehicle based on the power analysis information, and generate suspension adjustment strategy information; the power adjustment terminal is used to perform power adjustment strategy analysis of the unmanned vehicle based on the power analysis information, and generate power adjustment strategy information; the adjustment execution terminal is used to execute adjustment strategies in the suspension adjustment strategy information and the power adjustment strategy information;

[0037] The sensor data acquisition terminal includes a suspension sensor module, a vehicle condition sensor module and an environment sensor module; the suspension sensor module is used to collect suspension sensor data of the unmanned vehicle suspension system in real time; the vehicle condition sensor module is used to obtain real-time vehicle condition sensor data of the unmanned vehicle; the environment sensor module is used to obtain environmental sensor data of the external environment.

[0038] Optionally, the power assistance analysis terminal includes a data preprocessing module, a behavior recognition module and a power assistance analysis module; the data preprocessing module is used to preprocess the sensor data from the suspension sensor module, the vehicle condition sensor module and the environmental sensor module to eliminate noise and redundant information; the behavior recognition module is used to identify the current driving behavior pattern of the unmanned vehicle and changes in the driving environment based on the preprocessed sensor data; the power assistance analysis module is used to perform power assistance behavior analysis based on the driving behavior pattern, changes in the driving environment and sensor data to generate power assistance analysis information.

[0039] Optionally, the suspension adjustment terminal includes a suspension adjustment strategy analysis module, a suspension instruction generation module and a suspension adjustment strategy information generation module; the suspension adjustment strategy analysis module is used to perform suspension adjustment analysis based on power assistance analysis information; the suspension instruction generation module is used to generate suspension instructions based on the suspension adjustment analysis results; the suspension adjustment strategy information generation module is used to generate suspension adjustment strategy information based on the suspension instructions.

[0040] Optionally, the power adjustment terminal includes a power adjustment strategy analysis module, a power instruction generation module and a power adjustment strategy information generation module; the power adjustment strategy analysis module is used to perform power adjustment analysis based on the power assistance analysis information; the power instruction generation module is used to generate a power instruction based on the power adjustment analysis results; the power adjustment strategy information generation module is used to generate power adjustment strategy information based on the power instruction.

[0041] Optionally, the adjustment execution terminal includes a suspension execution module, a power execution module and a control feedback module; the suspension execution module is used to control the working parameters of the suspension system of the unmanned vehicle according to the suspension adjustment strategy information; the power execution module is used to adjust the power output of the power system of the unmanned vehicle according to the power adjustment strategy information; the control feedback module is used to monitor the execution effects of the suspension system and the power system in real time.

[0042] Optional, combined Figure 2 As shown, the suspension adjustment strategy analysis module includes a suspension analysis parameter extraction submodule and a suspension stiffness adjustment index calculation submodule; the suspension analysis parameter extraction submodule is used to extract suspension analysis parameters according to power analysis information; the suspension stiffness adjustment index calculation submodule is used to calculate the current suspension stiffness adjustment index of the unmanned vehicle according to the suspension analysis parameters.

[0043] Specifically, when the suspension stiffness adjustment index calculation submodule calculates, the following formula is satisfied:

[0044] f(Δθ)=cos 2 (Δθ)+β·(1-cos2 (Δθ));

[0045] Where H(t) represents the suspension stiffness adjustment index of the unmanned vehicle at time t during driving; Q i (t) represents the slope measurement value of the i-th road condition sensor on the unmanned vehicle; n represents the total number of road condition sensors on the unmanned vehicle; E j (t) represents the temperature measurement value of the jth environmental sensor on the unmanned vehicle; m represents the total number of environmental sensors on the unmanned vehicle; α represents the wind coefficient. The larger the size of the unmanned vehicle, the larger the wind coefficient. The specific value is set by the administrator based on experience; W k (t) represents the wind impact score of the kth wind sensor on the unmanned vehicle; q represents the total number of wind sensors on the unmanned vehicle; ρ represents the air density, which is generally 1.225 kg / ㎡; v w(t) represents the wind speed detection value of the kth wind sensor on the unmanned vehicle; C d A represents the air resistance constant of the unmanned vehicle, which is obtained as a known constant through wind tunnel experiments or vehicle design parameters; c represents the side area of ​​the unmanned vehicle; f(Δθ) represents the wind correction function; Δθ represents the angle difference between the current driving direction of the unmanned vehicle and the wind direction detected by the kth wind sensor; β represents the correction coefficient. The greater the wind speed in the weather forecast information corresponding to the location of the unmanned vehicle, the greater the correction coefficient. The specific value is set by the administrator based on experience.

[0046] The suspension instruction generation module includes a suspension gear selection submodule and a suspension instruction generation submodule; the suspension gear selection submodule is used to select the suspension gear according to the suspension stiffness adjustment index; the suspension instruction generation submodule is used to generate the corresponding suspension instruction according to the suspension gear. When the suspension gear selection submodule is working, the following formula is satisfied:

[0047]

[0048] Among them, D w Indicates the suspension gear position; h1 to h4 represent different gear selection thresholds, which are set by the administrator based on experience; D w =1 means suspension gear 1, and the corresponding suspension stiffness parameter range is: 150 to 300N / m; D w =2 means suspension gear 2, and the corresponding suspension stiffness parameter range is: 300 to 600N / m; D w =2 means suspension gear 2, and the corresponding suspension stiffness parameter range is: 600 to 800N / m; D w =3 means suspension position 3, and the corresponding suspension stiffness parameter range is: 800 to 1200N / m; D w=5 means suspension position 5, and the corresponding suspension stiffness parameter range is: 1200 to 2000N / m.

[0049] The following is the program code for the suspension stiffness adjustment index calculation process and the suspension gear selection process:

[0050]

[0051]

[0052]

[0053] Optional, combined Figure 3 As shown, the power adjustment strategy analysis module includes a power analysis parameter extraction submodule and a power output adjustment index calculation submodule; the power analysis parameter extraction submodule is used to extract power analysis parameters according to the power analysis information; the power output adjustment index calculation submodule is used to calculate the current power output adjustment index of the unmanned vehicle according to the power analysis parameters.

[0054] A control method for a self-powered system, applied to a self-powered system as described above, combined with Figure 4 As shown, the control method of the self-powered system includes:

[0055] S1, obtaining suspension sensor data, vehicle condition sensor data and environment sensor data of the unmanned vehicle;

[0056] S2, analyzing the power assist behavior according to the suspension sensor data, the environment sensor data and the vehicle condition sensor data, and generating power assist analysis information;

[0057] S3, performing suspension adjustment strategy analysis on the unmanned vehicle according to the power analysis information, and generating suspension adjustment strategy information;

[0058] S4, performing power adjustment strategy analysis on the unmanned vehicle according to the power analysis information, and generating power adjustment strategy information;

[0059] S5, executing the adjustment strategies in the suspension adjustment strategy information and the power adjustment strategy information.

[0060] In summary, by setting up the sensor data acquisition terminal, the suspension system, vehicle condition and environmental sensor data of the unmanned vehicle can be collected in real time, which can comprehensively reflect the operating status of the unmanned vehicle and the changes in the external environment. This setting is conducive to the realization of all-round and multi-level real-time monitoring of the unmanned vehicle, and thus provide accurate data support for the subsequent power analysis, suspension adjustment and power adjustment; through the setting of the power analysis terminal, especially the coordinated work of the data preprocessing module, the behavior recognition module and the power analysis module, the noise and redundant information in the sensor data can be effectively removed, the driving behavior pattern and environmental changes can be accurately identified, and then the power analysis information can be generated according to these analysis results. This setting is conducive to the dynamic understanding of the current driving state of the unmanned vehicle, and then provide a scientific basis for the suspension and power adjustment strategy of the vehicle; through the setting of the suspension adjustment terminal, combined with the coordinated work of the suspension adjustment strategy analysis module, the suspension instruction generation module and the suspension adjustment strategy information generation module, the suspension system of the unmanned vehicle can be efficiently analyzed and adjusted according to the power analysis information, and then accurate suspension adjustment strategy information can be generated. This setting is conducive to optimizing the performance of the suspension system in real time according to different road conditions and driving environments; through the setting of the power adjustment terminal, especially the cooperation of the power adjustment strategy analysis module, the power command generation module and the power adjustment strategy information generation module, the vehicle's power system can be optimized and adjusted according to the power analysis information; through the setting of the adjustment execution terminal, combined with the coordinated work of the suspension execution module, the power execution module and the control feedback module, the suspension and power adjustment strategies can be accurately executed, and the working status of the suspension system and the power system can be monitored and adjusted in real time. This setting is conducive to ensuring that the adjustment of the suspension system and the power system can be carried out according to the predetermined strategy, thereby maintaining the best performance of the unmanned vehicle during driving; through the setting of the suspension adjustment strategy analysis module, especially the coordinated work of the suspension analysis parameter extraction submodule and the suspension stiffness adjustment index calculation submodule, the key suspension parameters can be accurately extracted and the current suspension stiffness adjustment index can be calculated, thereby optimizing the suspension hardness adjustment strategy. This setting is conducive to dynamically adjusting the hardness of the suspension system according to the real-time driving status and changes in external road conditions; through the setting of the power adjustment strategy analysis module, combined with the work of the power analysis parameter extraction submodule and the power output adjustment index calculation submodule, the current power output adjustment index can be accurately extracted and calculated based on the power analysis information, thereby providing a scientific basis for the adjustment of the power system. This setting is conducive to automatically adjusting the power output according to changes in the vehicle's load, speed, road conditions, etc., to achieve efficient energy management and power demand matching; through the suspension selection algorithm, the changes in external environmental wind speed, wind direction and wind force can be considered during the adjustment of the suspension system of unmanned vehicles. By incorporating these wind factors into the suspension hardness adjustment formula, it is conducive to optimizing the responsiveness of the suspension system and reducing the negative impact of wind force on vehicle driving stability.Furthermore, the suspension stiffness can be adjusted in real time to adapt to the force exerted on the vehicle by changes in wind speed, thereby improving the driving stability of unmanned vehicles under complex weather conditions, especially in the case of high wind speed or unstable wind force, ensuring the rapid response of the vehicle suspension system and the safety of the vehicle. At the same time, this embodiment also takes the environmental parameter temperature into consideration, because high temperature can cause the rubber bushings and buffer elements in the suspension system to soften, reducing the overall rigidity. Increasing the spring stiffness can offset this softening and maintain the support and response speed of the suspension system. High temperature may increase the tire pressure or reduce the road adhesion. Increasing the suspension stiffness can optimize the contact area between the tire and the ground, reduce roll and pitch, and improve steering accuracy and dynamic stability. The expansion of metal parts at high temperatures may change the suspension geometry parameters (such as camber angle, toe angle), and moderately increasing the stiffness can reduce the impact of deformation on the dynamic performance of the vehicle. Long-term high temperature may cause spring metal fatigue or deterioration of shock absorber oil performance. Increasing the stiffness can reduce the compression stroke during severe bumps and prevent the chassis from colliding with the ground. Unmanned vehicles rely on high-precision sensors (such as LiDAR and cameras). Improving rigidity can suppress high-frequency shaking of the vehicle body, ensure stable sensor data, and avoid navigation and decision-making errors. A harder suspension system reduces high-frequency vibration and reciprocating motion of components, reduces heat generated by friction, and indirectly alleviates heat load pressure in high-temperature environments.

[0061] Embodiment 2: This embodiment includes all the contents of Embodiment 1 and provides a self-power-assisting system, wherein the power adjustment strategy analysis module includes a power analysis parameter extraction submodule and a power output adjustment index calculation submodule; the power analysis parameter extraction submodule is used to extract power analysis parameters based on power-assisting analysis information; the power output adjustment index calculation submodule is used to calculate the current power output adjustment index of the unmanned vehicle based on the power analysis parameters.

[0062] When the power output adjustment index calculation submodule calculates, the following formula is satisfied:

[0063]

[0064] R b (t) = H d ·(1+0.2·d l (t)·v(t));

[0065]

[0066] Where P represents the power output adjustment index of the unmanned vehicle at time t during driving; F i represents the noise amplitude data of the i-th noise sensor in the unmanned vehicle at time t; n represents the total number of noise sensors in the unmanned vehicle; R b (t) represents the road condition impact score of the bth wheel on the unmanned vehicle; Hd Indicates the suspension stiffness corresponding to the current suspension gear position of the unmanned vehicle; d l (t) represents the road surface roughness under the bth wheel at time t, which is obtained by a laser-type roughness sensor; B represents the total number of wheels of the unmanned vehicle; v(t) represents the speed of the unmanned vehicle at time t; α represents the wind force coefficient. The larger the size of the unmanned vehicle, the larger the wind force coefficient. The specific value is set by the administrator based on experience; V(t) represents the vibration impact index value at time t; λ i represents the vibration influence coefficient of the i-th vibration sensor. The closer the vibration sensor is to the center of the unmanned vehicle, the greater the vibration influence coefficient. The specific value is set by the administrator based on experience. N represents the total number of vibration sensors. A i (t) represents the vibration amplitude of the i-th vibration sensor at time t; f i (t) represents the vibration frequency of the i-th vibration sensor at time t.

[0067] The power command generation module includes a power output gear selection submodule and a power command generation submodule; the power output gear selection submodule is used to select the power output gear according to the power output adjustment index; the power command generation submodule is used to generate a corresponding power command according to the power output gear. When the power output gear selection submodule is working, the following formula is satisfied:

[0068]

[0069] Among them, D d Indicates the power output gear; p1 to p4 represent different gear selection thresholds, which are set by the administrator based on experience; D d =1 means power output gear 1, the corresponding power parameter range is: 10 to 30kW; D d =2 means power output gear 2, the corresponding power parameter range is: 30 to 60kW; D d =3 means power output gear 3, the corresponding power parameter range is: 60 to 100kW; D d =4 means power output gear 4, the corresponding power parameter range is: 100 to 120kW; D d =5 means power output gear 5, and the corresponding power parameter range is: 120 to 150kW.

[0070] The following is the program code for the suspension stiffness adjustment index calculation process and the suspension gear selection process:

[0071]

[0072]

[0073]

[0074] In summary, through the power output selection algorithm and the introduction of internal vibration factors, the impact of vibration frequencies and vibration amplitudes at different positions on the vehicle suspension system and power system can be considered. Incorporating vibration factors into the power output adjustment formula is conducive to real-time adjustment of the power output of the power system according to the vibration conditions of different parts of the vehicle, preventing the vehicle from being unbalanced or damaged due to excessive vibration. Furthermore, during dynamic driving, the power output is optimized according to the vibration data, and the driving stability of the vehicle is improved, thereby improving the control accuracy of the unmanned vehicle, especially at high speeds or complex road conditions, which can better eliminate unnecessary vibration interference.

[0075] The contents disclosed above are only preferred feasible embodiments of the present invention, and do not limit the protection scope of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention description and drawings are included in the protection scope of the present invention. In addition, the elements therein can be updated as technology develops.

Claims

1. A self-powered system, characterized in that: It includes a sensor data acquisition terminal, a power analysis terminal, a suspension adjustment terminal, a power adjustment terminal and an adjustment execution terminal; the sensor data acquisition terminal is used to acquire the suspension sensor data, vehicle condition sensor data and environment sensor data of the unmanned vehicle; the power analysis terminal is used to perform power behavior analysis based on the suspension sensor data, environment sensor data and vehicle condition sensor data to generate power analysis information; the suspension adjustment terminal is used to perform suspension adjustment strategy analysis of the unmanned vehicle based on the power analysis information to generate suspension adjustment strategy information; The power adjustment terminal is used to analyze the power adjustment strategy of the unmanned vehicle according to the power analysis information to generate power adjustment strategy information; the adjustment execution terminal is used to execute the adjustment strategy in the suspension adjustment strategy information and the power adjustment strategy information; The sensor data acquisition terminal includes a suspension sensor module, a vehicle condition sensor module and an environment sensor module; the suspension sensor module is used to collect suspension sensor data of the unmanned vehicle suspension system in real time; the vehicle condition sensor module is used to obtain real-time vehicle condition sensor data of the unmanned vehicle; the environment sensor module is used to obtain environmental sensor data of the external environment.

2. A self-powered system as claimed in claim 1, characterized in that: The power-assist analysis terminal includes a data preprocessing module, a behavior recognition module and a power-assist analysis module; the data preprocessing module is used to preprocess the sensor data from the suspension sensor module, the vehicle condition sensor module and the environment sensor module to eliminate noise and redundant information; the behavior recognition module is used to identify the current driving behavior pattern of the unmanned vehicle and the changes in the driving environment based on the preprocessed sensor data; the power-assist analysis module is used to perform power-assist behavior analysis based on the driving behavior pattern, the changes in the driving environment and the sensor data to generate power-assist analysis information.

3. A self-powered system as claimed in claim 2, characterized in that: The suspension adjustment terminal includes a suspension adjustment strategy analysis module, a suspension instruction generation module and a suspension adjustment strategy information generation module; the suspension adjustment strategy analysis module is used to perform suspension adjustment analysis based on power assistance analysis information; the suspension instruction generation module is used to generate suspension instructions based on the suspension adjustment analysis results; the suspension adjustment strategy information generation module is used to generate suspension adjustment strategy information based on the suspension instructions.

4. A self-powered system as claimed in claim 3, characterized in that: The power adjustment terminal includes a power adjustment strategy analysis module, a power instruction generation module and a power adjustment strategy information generation module; the power adjustment strategy analysis module is used to perform power adjustment analysis based on the power assistance analysis information; the power instruction generation module is used to generate a power instruction based on the power adjustment analysis results; the power adjustment strategy information generation module is used to generate power adjustment strategy information based on the power instruction.

5. A self-powered system as claimed in claim 4, characterized in that: The adjustment execution terminal includes a suspension execution module, a power execution module and a control feedback module; the suspension execution module is used to control the working parameters of the suspension system of the unmanned vehicle according to the suspension adjustment strategy information; the power execution module is used to adjust the power output of the power system of the unmanned vehicle according to the power adjustment strategy information; the control feedback module is used to monitor the execution effects of the suspension system and the power system in real time.

6. A self-powered system as claimed in claim 5, characterized in that: The suspension adjustment strategy analysis module includes a suspension analysis parameter extraction submodule and a suspension stiffness adjustment index calculation submodule; the suspension analysis parameter extraction submodule is used to extract suspension analysis parameters according to power analysis information; the suspension stiffness adjustment index calculation submodule is used to calculate the current suspension stiffness adjustment index of the unmanned vehicle according to the suspension analysis parameters.

7. A self-powered system as claimed in claim 6, characterized in that: The power adjustment strategy analysis module includes a power analysis parameter extraction submodule and a power output adjustment index calculation submodule; the power analysis parameter extraction submodule is used to extract power analysis parameters according to the power analysis information; the power output adjustment index calculation submodule is used to calculate the current power output adjustment index of the unmanned vehicle according to the power analysis parameters.

8. A control method for a self-powered system, applied to a self-powered system as claimed in claim 7, characterized in that: The control method of the self-powered system comprises: S1, obtaining suspension sensor data, vehicle condition sensor data and environment sensor data of the unmanned vehicle; S2, analyzing the power assist behavior according to the suspension sensor data, the environment sensor data and the vehicle condition sensor data, and generating power assist analysis information; S3, performing suspension adjustment strategy analysis on the unmanned vehicle according to the power analysis information, and generating suspension adjustment strategy information; S4, performing power adjustment strategy analysis on the unmanned vehicle according to the power analysis information, and generating power adjustment strategy information; S5, executing the adjustment strategies in the suspension adjustment strategy information and the power adjustment strategy information.

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