Intelligent frequency selection system for vehicle-mounted ultra-short wave radio
Patent Information
- Application Number
- CN202411471133.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-21
- Publication Date
- 2026-10-23
AI Technical Summary
[0005]针对现有技术的不足，本发明提供了用于车载超短波电台的智能频率选择系统，解决了新能源电力输送系统在复杂场景下(城市、高速公路或山区)也面临着线路故障、负载波动及传输路径拥塞问题
[0044]1、本发明，多场景环境感知与自适应频率选择策略，能够有效应对复杂动态环境(包括城市、高速公路和山区)下的多种通信干扰与环境波动，具体来说，多场景环境感知模块通过采集多维度环境特征数据(包括信号强度、干扰噪声、地形类型和车辆移动状态)并进行深度场景识别与实时环境预测，在环境剧烈变化(包括通信信号被建筑物反射、山区地形的多路径效应或高速公路的快速干扰切换)时，能够提前识别潜在风险，并自适应调整频率选择策略，确保车载超短波电台在复杂场景中始终保持高质量的通信链路，从而大幅度提升了系统在动态环境中的通信稳定性和可靠性。
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Abstract
Description
Technical Field
[0001] This invention relates to the field of vehicle-mounted VHF radios, specifically to an intelligent frequency selection system for vehicle-mounted VHF radios. Background Technology
[0002] With the rapid development of vehicle-mounted communication technology, UHF radios play an important role in vehicle-mounted communication, traffic control, and emergency communication. However, in practical applications, vehicle-mounted radios face extremely complex communication environments, often affected by factors such as building reflections, terrain obstructions, environmental interference, and signal overlap, leading to unstable communication signals and low frequency band switching efficiency. At the same time, new energy power transmission systems also face problems such as line faults, load fluctuations, and transmission path congestion in complex scenarios (such as cities, highways, or mountainous areas). These problems are particularly prominent in dynamic and complex environments. Therefore, an intelligent frequency selection and power transmission optimization system that can adapt to complex environmental changes is needed to ensure the stability and continuity of vehicle-mounted communication and power systems.
[0003] In existing technologies, frequency selection schemes for vehicle communication systems often employ fixed frequency band switching or simple interference detection strategies. These methods tend to rely on a single signal strength or interference index for frequency band switching, lacking in-depth perception and comprehensive analysis of the multi-dimensional communication environment. They are unable to cope with frequent channel fluctuations or complex environmental changes. For example, when a vehicle radio encounters building reflection interference in urban roads, existing frequency switching strategies usually cannot respond in time, easily leading to communication link interruption or signal quality degradation. In addition, traditional frequency band switching methods often adopt passive triggering switching strategies, adjusting the frequency band only when the signal quality deteriorates significantly, resulting in low system response speed and switching efficiency.
[0004] To address the aforementioned problems, this invention proposes an intelligent frequency selection system for vehicle-mounted VHF radios. Summary of the Invention
[0005] To address the shortcomings of existing technologies, this invention provides an intelligent frequency selection system for vehicle-mounted VHF radios, which solves the problems of line faults, load fluctuations, and transmission path congestion faced by new energy power transmission systems in complex scenarios (cities, highways, or mountainous areas).
[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent frequency selection system for vehicle-mounted VHF radios, comprising the following modules:
[0007] The multi-scenario environment perception module is used to collect information on the current environment's communication frequency band status, power load status, and geographical environment through various sensors, and to classify the current scenario and predict the dynamic environmental status.
[0008] The intelligent frequency selection module is used to select frequency bands and switch dynamically based on the scene classification results and frequency band health information provided by the multi-scene environment perception module and an adaptive frequency selection algorithm.
[0009] The power transmission optimization module is used to dynamically adjust the power transmission path based on the health assessment of power transmission lines and load distribution information, so as to achieve the optimal power dispatch strategy.
[0010] The communication and power joint optimization module is used to achieve coordinated optimization of communication frequency bands and power transmission paths through multi-objective optimization algorithms when communication frequency bands are interfered with or power path failures occur.
[0011] The linkage control module is used to coordinate and adjust the frequency band and power dispatch through real-time linkage strategies when there are abnormalities in the communication frequency band or power transmission path.
[0012] The redundancy switching and fault recovery module is used to activate the redundant frequency band and backup path library and perform rapid fault recovery and switching when communication frequency band or power path failure occurs.
[0013] Preferably, the multi-scene environment perception module further includes:
[0014] The data acquisition submodule is used to collect various environmental characteristic data, including communication frequency band characteristic data (including signal strength, signal-to-noise ratio, and frequency band occupancy status), power load characteristic data (including line voltage, current, load density, and line impedance), and environmental status characteristic data (including geographic information, terrain perception, and road status).
[0015] The scene recognition submodule is used to extract features from the collected data and identify the current scene using a machine learning-based classification model to generate scene labels.
[0016] The dynamic environment prediction submodule is used to make short-term (1-5 seconds) predictions of future environmental conditions using a time-series prediction model and output environmental condition warning signals.
[0017] The environmental health assessment submodule is used to assess the health of each frequency band, load path, and environmental characteristics, and generate an environmental health index (a score between 0 and 1).
[0018] Preferably, the intelligent frequency selection module further includes:
[0019] The frequency band health assessment submodule is used to comprehensively assess the signal strength, signal-to-noise ratio, bandwidth utilization, and interference status of all available communication frequency bands based on fuzzy logic algorithms, and to calculate the health score of each frequency band.
[0020] The adaptive frequency selection submodule is used to select the optimal frequency band based on reinforcement learning algorithms (including DQN algorithm) and the current scene label and frequency band health score.
[0021] The frequency band switching control submodule is used to detect when the signal quality of the current frequency band deteriorates or interference increases. It then uses an interference source identification and prediction model to determine the type of interference and initiate a frequency band switching strategy.
[0022] The frequency band switching smoothing submodule is used to perform short-term parallel transmission between the old and new frequency bands during frequency band switching using a gradual switching strategy, ensuring the continuity of data transmission and communication quality.
[0023] Preferably, the power transmission optimization module further includes:
[0024] The power path health assessment submodule is used to calculate the health of each power transmission path in real time based on voltage stability, load density, and current fluctuation characteristic parameters, and generate a health score.
[0025] The dynamic load scheduling submodule is used to dynamically adjust the power transmission strategy based on the health of the current power transmission path and the load distribution information, using a multi-objective optimization algorithm.
[0026] The power path selection and switching submodule is used to activate the load distribution and switching strategy of the backup power path when the health score of a power transmission path is detected to be lower than a preset threshold.
[0027] Preferably, the communication and power joint optimization module further includes:
[0028] The multi-objective optimization submodule is used to perform joint optimization based on multiple objectives such as communication signal quality, power transmission health, and system operation stability, using multi-objective optimization algorithms (including MOEA / D).
[0029] The joint strategy decision-making submodule is used to select the optimal combination strategy of communication frequency band and power path based on Pareto front theory, and to adjust the global scheduling scheme of the system in real time.
[0030] Preferably, the linkage control module further includes:
[0031] The frequency band and power path linkage submodule is used to adjust the load distribution strategy of the power path when interference occurs in the communication frequency band, and to prioritize the communication frequency band with the best signal quality when the power path fails.
[0032] The dynamic recovery and adjustment submodule is used to adjust the linkage strategy between communication and power according to the dynamic changes in real-time environmental conditions and load requirements.
[0033] Preferably, the redundancy switching and fault recovery module further includes:
[0034] The redundant frequency band and path library management submodule is used to establish multiple redundant frequency bands and power path libraries, and to dynamically update them according to real-time environmental conditions and path health.
[0035] The fast fault recovery submodule is used to activate the fast fault recovery strategy when a communication frequency band or power path fault is detected. It selects the backup frequency band or path with the highest health and completes the fault switching and system recovery within 10ms.
[0036] Preferably, the system further includes an adaptive weight adjustment module, which is used to dynamically adjust the weight values of different optimization objectives according to the current environmental state and the priority of the optimization objectives, so as to achieve adaptive optimization trade-offs.
[0037] Preferably, the adaptive frequency selection submodule in the intelligent frequency selection module further employs a multi-level optimization algorithm, including:
[0038] The global search hierarchy is used to perform a global band search across all available communication bands and select the potentially optimal band.
[0039] Local fine-tuning hierarchy is used to fine-tune local parameters in the globally optimal frequency band, thereby improving the utilization rate of communication frequency bands and signal quality.
[0040] Preferably, all modules integrated in the system can be uniformly scheduled through a central controller, and data interaction and collaborative work between multiple modules can be realized based on dynamic perception and adaptive optimization strategies. The central controller further includes:
[0041] The data storage module is used to store environmental data, historical frequency band usage data, and power transmission status information;
[0042] The decision engine module is used to make comprehensive decisions on the current strategy based on a multi-objective optimization model, and output the optimal communication frequency band and power path strategy.
[0043] This invention provides an intelligent frequency selection system for vehicle-mounted VHF radios. It offers the following advantages:
[0044] 1. This invention, with its multi-scenario environmental perception and adaptive frequency selection strategy, can effectively cope with various communication interferences and environmental fluctuations in complex dynamic environments (including urban areas, highways, and mountainous regions). Specifically, the multi-scenario environmental perception module collects multi-dimensional environmental feature data (including signal strength, interference noise, terrain type, and vehicle movement status) and performs deep scene recognition and real-time environmental prediction. When the environment changes drastically (including communication signals being reflected by buildings, multipath effects in mountainous terrain, or rapid interference switching on highways), it can identify potential risks in advance and adaptively adjust the frequency selection strategy to ensure that the vehicle-mounted VHF radio maintains a high-quality communication link in complex scenarios, thereby significantly improving the communication stability and reliability of the system in dynamic environments.
[0045] 2. This invention achieves deep coupling and dynamic collaborative optimization of power transmission and communication systems in complex scenarios by designing a joint optimization module for communication and power. By introducing multi-objective optimization algorithms (MOEA / D and multi-objective decision-making strategies based on Pareto fronts), it can quickly adjust load distribution and communication strategies when there are fluctuations in communication frequency bands and power paths. It also performs global optimization selection by combining the health of communication frequency bands and the health of power paths, avoiding linkage failures caused by communication frequency band switching or power path failures.
[0046] 3. This invention combines a time-series prediction model (including LSTM and GRU) with a risk warning algorithm, enabling short-term prediction of future environmental conditions, identification of potential faults or signal interference risks in communication frequency bands and power transmission paths, and early warning signals for proactive strategy adjustments. When a decline in frequency band signal quality or a power transmission path health level below a preset threshold is detected, the redundancy switching and fault recovery module can quickly switch and restore the system in a short time using a preset redundant frequency band and backup path library, ensuring that the system can respond and adjust rapidly in complex environments. Attached Figure Description
[0047] Figure 1 This is a framework diagram of the intelligent frequency selection system of the present invention;
[0048] Figure 2 This is a framework diagram of the multi-scene environment perception module of the present invention;
[0049] Figure 3 This is a framework diagram of the intelligent frequency selection module of the present invention;
[0050] Figure 4 This is a framework diagram of the power transmission optimization module of the present invention;
[0051] Figure 5 This is a framework diagram of the communication and power joint optimization module of the present invention;
[0052] Figure 6 This is a framework diagram of the linkage control module of the present invention;
[0053] Figure 7 This is a framework diagram of the redundancy switching and fault recovery module of the present invention;
[0054] Figure 8 This is a framework diagram of the adaptive weight adjustment module of the present invention;
[0055] Figure 9 This is a diagram of the central controller framework of the present invention. Detailed Implementation
[0056] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0057] Example 1:
[0058] Please see the appendix Figure 1 - Appendix Figure 9 This invention provides an intelligent frequency selection system for vehicle-mounted VHF radios, comprising the following modules:
[0059] The multi-scenario environment perception module is used to collect information on the current environment's communication frequency band status, power load status, and geographical environment through various sensors, and to classify the current scenario and predict the dynamic environmental status.
[0060] The intelligent frequency selection module is used to select frequency bands and switch dynamically based on the scene classification results and frequency band health information provided by the multi-scene environment perception module and an adaptive frequency selection algorithm.
[0061] The power transmission optimization module is used to dynamically adjust the power transmission path based on the health assessment of power transmission lines and load distribution information, so as to achieve the optimal power dispatch strategy.
[0062] The communication and power joint optimization module is used to achieve coordinated optimization of communication frequency bands and power transmission paths through multi-objective optimization algorithms when communication frequency bands are interfered with or power path failures occur.
[0063] The linkage control module is used to coordinate and adjust the frequency band and power dispatch through real-time linkage strategies when there are abnormalities in the communication frequency band or power transmission path.
[0064] The redundancy switching and fault recovery module is used to activate the redundant frequency band and backup path library and perform rapid fault recovery and switching when communication frequency band or power path failure occurs.
[0065] The multi-scene environment perception module further includes:
[0066] The data acquisition submodule is used to collect various environmental characteristic data, including communication frequency band characteristic data (including signal strength, signal-to-noise ratio, and frequency band occupancy status), power load characteristic data (including line voltage, current, load density, and line impedance), and environmental status characteristic data (including geographic information, terrain perception, and road status).
[0067] The scene recognition submodule is used to extract features from the collected data and identify the current scene using a machine learning-based classification model to generate scene labels.
[0068] The dynamic environment prediction submodule is used to make short-term (1-5 seconds) predictions of future environmental conditions using a time-series prediction model and output environmental condition warning signals.
[0069] The environmental health assessment submodule is used to assess the health of each frequency band, load path, and environmental characteristics, and generate an environmental health index (a score between 0 and 1).
[0070] Specifically, the data acquisition submodule is used to collect various characteristic data such as communication frequency bands (signal strength, signal-to-noise ratio, frequency band occupancy status), power load (voltage, current, load density, line impedance), and environmental conditions (geographic information, terrain perception, road conditions) through multiple sensors, and performs data preprocessing; the scene recognition submodule extracts features from the collected data using machine learning-based models (such as neural networks or support vector machines), identifies the current scene, and generates scene labels (such as city, highway, or mountainous area); the dynamic environment prediction submodule uses time series models (such as LSTM, GRU) to make short-term predictions of the environmental conditions for the next 15 seconds, identifies signal fluctuation risks in advance, and outputs early warning signals; the environmental health assessment submodule comprehensively evaluates each frequency band, load path, and environmental characteristics, and generates a health score between 0 and 1 to guide subsequent frequency and power dispatch optimization strategies.
[0071] The intelligent frequency selection module further includes:
[0072] The frequency band health assessment submodule is used to comprehensively assess the signal strength, signal-to-noise ratio, bandwidth utilization, and interference status of all available communication frequency bands based on fuzzy logic algorithms, and to calculate the health score of each frequency band.
[0073] The adaptive frequency selection submodule is used to select the optimal frequency band based on reinforcement learning algorithms (including DQN algorithm) and the current scene label and frequency band health score;
[0074] The frequency band switching control submodule is used to detect when the signal quality of the current frequency band deteriorates or interference increases. It then uses an interference source identification and prediction model to determine the type of interference and initiate a frequency band switching strategy.
[0075] The frequency band switching smoothing submodule is used to perform short-term parallel transmission between the old and new frequency bands during frequency band switching using a gradual switching strategy, ensuring the continuity of data transmission and communication quality.
[0076] Specifically, the frequency band health assessment submodule uses a fuzzy logic algorithm to comprehensively evaluate the signal strength, signal-to-noise ratio, bandwidth utilization, and interference status of all available communication frequency bands, calculating a health score for each band as the basis for frequency band selection. The adaptive frequency selection submodule uses a reinforcement learning algorithm (DQN algorithm) to dynamically select the optimal communication frequency band by combining the current scene label and the frequency band health score. The frequency band switching control submodule is used to determine the interference type through an interference source identification model and initiate a frequency band switching strategy when a decline in the signal quality or an increase in interference is detected in the current frequency band, thereby achieving rapid frequency band switching. The frequency band switching smoothing submodule uses a gradual switching strategy to perform short-term parallel transmission between the old and new frequency bands during frequency band switching, ensuring a smooth transition of data transmission, thereby avoiding data loss and communication interruption, and improving the continuity and stability of communication.
[0077] The power transmission optimization module further includes:
[0078] The power path health assessment submodule is used to calculate the health of each power transmission path in real time based on voltage stability, load density, and current fluctuation characteristic parameters, and generate a health score.
[0079] The dynamic load scheduling submodule is used to dynamically adjust the power transmission strategy based on the health of the current power transmission path and the load distribution information, using a multi-objective optimization algorithm.
[0080] The power path selection and switching submodule is used to activate the load distribution and switching strategy of the backup power path when the health score of a power transmission path is detected to be lower than a preset threshold.
[0081] Specifically, the power path health assessment submodule is used to calculate the health of each power transmission path in real time based on characteristic parameters such as voltage stability, load density, and current fluctuation, and generate a health score as the basis for path selection; the dynamic load scheduling submodule uses a multi-objective optimization algorithm to dynamically adjust the power transmission strategy according to the health score of each path and the current load distribution to optimize load balancing and transmission efficiency; the power path selection and switching submodule is used to automatically activate the load allocation and switching strategy of the backup path when the health score of a power transmission path is lower than a preset threshold, to ensure the continuity and stability of power transmission and avoid power interruption caused by path failure.
[0082] The joint optimization module for communication and power further includes:
[0083] The multi-objective optimization submodule is used to perform joint optimization based on multiple objectives such as communication signal quality, power transmission health, and system operation stability, using multi-objective optimization algorithms (including MOEA / D).
[0084] The joint strategy decision-making submodule is used to select the optimal combination strategy of communication frequency band and power path based on Pareto front theory, and to adjust the global scheduling scheme of the system in real time.
[0085] The linkage control module further includes:
[0086] The frequency band and power path linkage submodule is used to adjust the load distribution strategy of the power path when interference occurs in the communication frequency band, and to prioritize the communication frequency band with the best signal quality when the power path fails.
[0087] The dynamic recovery and adjustment submodule is used to adjust the linkage strategy between communication and power according to the dynamic changes in real-time environmental conditions and load requirements.
[0088] Specifically, the multi-objective optimization submodule, based on the multi-objective optimization algorithm (MOEA / D), comprehensively considers communication signal quality, power path health, and system operational stability for joint optimization, balancing the trade-offs between various objectives. The joint strategy decision submodule, based on Pareto front theory, selects the optimal communication frequency band and power path combination strategy from multiple feasible solutions and dynamically adjusts the global scheduling scheme according to real-time changes in the environment and load. The linkage control module includes the following submodules: a frequency band and power path linkage submodule, which prioritizes adjusting the power load allocation strategy to reduce the impact of communication fluctuations when interference occurs in the communication frequency band, and prioritizes switching to the communication frequency band with the best signal quality when the power path fails; and a dynamic recovery and adjustment submodule, which adjusts the communication and power linkage strategy in a timely manner according to the dynamic changes in real-time environmental conditions and load demands, ensuring stable operation of the system in complex scenarios.
[0089] The redundancy switching and fault recovery module further includes:
[0090] The redundant frequency band and path library management submodule is used to establish multiple redundant frequency bands and power path libraries, and to dynamically update them according to real-time environmental conditions and path health.
[0091] The fast fault recovery submodule is used to activate the fast fault recovery strategy when a communication frequency band or power path fault is detected. It selects the backup frequency band or path with the highest health and completes the fault switching and system recovery within 10ms.
[0092] The system also includes an adaptive weight adjustment module, which dynamically adjusts the weight values of different optimization objectives based on the current environmental state and the priority of the optimization objectives, thereby achieving adaptive optimization trade-offs.
[0093] The adaptive frequency selection submodule in the intelligent frequency selection module further employs a multi-level optimization algorithm, including:
[0094] The global search hierarchy is used to perform a global band search across all available communication bands and select the potentially optimal band.
[0095] Local fine-tuning hierarchy is used to fine-tune local parameters in the globally optimal frequency band, thereby improving the utilization rate of communication frequency bands and signal quality.
[0096] All modules integrated in the system can be uniformly scheduled through a central controller, and data interaction and collaborative work between multiple modules can be realized based on dynamic perception and adaptive optimization strategies. The central controller further includes:
[0097] The data storage module is used to store environmental data, historical frequency band usage data, and power transmission status information;
[0098] The decision engine module is used to make comprehensive decisions on the current strategy based on a multi-objective optimization model, and output the optimal communication frequency band and power path strategy.
[0099] Specifically, the redundant frequency band and path library management submodule is used to establish multiple redundant communication frequency bands and power path libraries, and to dynamically update and maintain them according to real-time environmental status and path health to ensure the effectiveness of backup solutions; the rapid fault recovery submodule immediately starts a rapid recovery strategy when a communication frequency band or power path failure is detected, selects the backup frequency band or path with the highest health, and completes the switching and system recovery within 10ms.
[0100] The system also includes an adaptive weight adjustment module, which dynamically adjusts the weights of each objective based on the current environmental state and the priorities of different optimization objectives, thereby achieving an adaptive balance of the optimization strategy.
[0101] The adaptive frequency selection submodule in the intelligent frequency selection module further employs a multi-level optimization algorithm, including: a global search level, which conducts a broad search across all available frequency bands to determine the potential optimal frequency band; and a local fine-tuning level, which further adjusts parameters within the globally optimal frequency band to improve communication frequency band utilization and signal quality.
[0102] All modules of the system are uniformly scheduled by the central controller, and data interaction and collaborative work between modules are realized based on dynamic perception and adaptive strategies.
[0103] The central controller also includes a data storage module for storing environmental data, historical frequency band usage records, and power transmission status information; and a decision engine module for comprehensively analyzing the current strategy based on a multi-objective optimization model and outputting the optimal scheduling scheme for communication frequency bands and power paths.
[0104] Example 2:
[0105] The system integrates multi-scenario environmental perception modules, intelligent frequency selection modules, power transmission optimization modules, communication and power joint optimization modules, linkage control modules, and redundancy switching and fault recovery modules to achieve adaptive optimization of vehicle-mounted radio communication frequencies and dynamic scheduling of power transmission paths in complex scenarios. This system can automatically adjust communication strategies and power transmission paths when the environment undergoes drastic changes (including encountering building reflections, terrain changes, or line faults), ensuring the continuity and stability of system operation.
[0106] 2. System Overall Architecture and Module Detailed Design
[0107] The overall architecture of the "Intelligent Frequency Selection System for Vehicle-Mounted VHF Radio" of the present invention consists of multiple sub-modules, and the functions of each module include the following:
[0108] 2.1 Multi-Scene Environment Perception Module
[0109] The core function of the multi-scenario environment perception module is to comprehensively and in real-time monitor and perceive the communication environment and power system operation status around the vehicle radio, and to perform multi-scenario classification, dynamic environment prediction and health assessment.
[0110] Working principle: The multi-scenario environment perception module collects environmental feature data through various sensors installed on the vehicle system (including communication frequency band status sensors, environmental status sensors, and load status sensors), generating multi-dimensional feature vectors. By introducing a deep learning-based scene classification model (including LSTM or Bayesian networks), the module identifies the current environment and predicts future environmental conditions through a dynamic prediction model (including GRU or time-series data analysis models), thus identifying potential interference sources or load fluctuations in advance.
[0111] Technical details:
[0112] Data acquisition submodule:
[0113] Multiple sensors are used to collect communication frequency band characteristic data (including signal strength RSS1, signal-to-noise ratio SNR, bandwidth utilization), power load characteristic data (including load current, voltage, power fluctuation), and environmental condition characteristic data (including terrain type, surrounding building information, vehicle location, etc.) in real time, and the raw data are uniformly formatted into standardized data vectors.
[0114] Scene recognition submodule:
[0115] A machine learning-based scene recognition model is used to classify the current environment into different scene labels (including urban roads, highways, and mountainous areas) through feature extraction and pattern matching.
[0116] Dynamic Environment Prediction Submodule:
[0117] Use time-series prediction models (including LSTM or GRU) to make short-term predictions (1-5 seconds) of the current environmental state and identify potential risks (including communication interference sources or power load fluctuations).
[0118] Environmental health assessment submodule:
[0119] The fuzzy logic algorithm is used to assess the health of all collected environmental feature data, calculate the signal health score (between 0 and 1) for each scenario, and transmit the assessment results to the intelligent frequency selection module and the communication-power joint optimization module.
[0120] Environmental health assessment model:
[0121] A fuzzy logic algorithm is used to perform a comprehensive health assessment for each scenario. The input variables are defined as environmental feature data {E1, E2, ..., E...}. n The system uses fuzzy rules to evaluate and generate a health score H.
[0122]
[0123] Where, μ i (E i Let w be the fuzzy membership function of the i-th feature. i The weighting coefficient is used, and the final health score H ranges from [0,1] to 0.
[0124] 2.2 Intelligent Frequency Selection Module
[0125] The core task of the intelligent frequency selection module is to dynamically select the optimal communication frequency band based on the scene tags and health information provided by the multi-scene environment perception module, and to achieve rapid switching when the signal quality of the frequency band deteriorates or interference increases.
[0126] Working principle: The intelligent frequency selection module uses a reinforcement learning-based frequency band selection algorithm (including DQN or Q-learning) to dynamically decide on all available frequency bands. This algorithm can optimize the frequency band selection strategy through interactive learning with the environment and switch to a better frequency band in a timely manner when signal quality deteriorates. The system also introduces a frequency band switching smoothing strategy, performing parallel transmission between old and new frequency bands to ensure communication continuity.
[0127] Technical details:
[0128] Frequency band health assessment submodule:
[0129] Fuzzy logic models are used to comprehensively evaluate indicators such as signal strength, bandwidth utilization, and interference noise, generating a health score for each frequency band.
[0130] Adaptive frequency selection submodule:
[0131] A frequency selection strategy based on reinforcement learning is introduced. The model's state is the environmental label and frequency band features, the action is the set of available frequency bands, and the reward is the improvement in communication quality.
[0132] Frequency band switching control submodule:
[0133] The design incorporates a frequency band switching strategy based on interference source identification and frequency band prediction. When the health of the current frequency band is detected to be below a threshold, the strategy immediately initiates frequency band switching and selects the optimal frequency band for communication.
[0134] 2.3 Power Transmission Optimization Module
[0135] The power transmission optimization module dynamically adjusts the power dispatching strategy by monitoring the health of the power transmission path (including voltage, current, load density, etc.) in real time, thereby achieving the optimal selection of power transmission paths and load allocation.
[0136] Working principle: The power transmission optimization module uses a dynamic load scheduling algorithm based on multi-objective optimization to calculate the health of all power paths in real time. When the load fluctuates or the power demand changes, it adjusts the power allocation strategy to select the optimal path and avoid excessive fluctuations and losses in power transmission.
[0137] Technical details:
[0138] Power path health assessment submodule:
[0139] Real-time health assessments are performed on all power paths, including indicators such as voltage fluctuations, load balancing, and equipment status, and a health score is generated.
[0140] Dynamic load scheduling submodule:
[0141] A multi-objective optimization algorithm (including NSGA-II) is used to optimize the dynamic scheduling strategy based on path health score, load demand changes, and environmental conditions.
[0142] Power path selection and switching submodule:
[0143] When the health of a path falls below a threshold, a path switching strategy is initiated to transfer the power load to a backup path.
[0144] Multi-objective optimization model formula:
[0145] The NSGA-II multi-objective optimization algorithm is adopted, based on the path health H. path Load balancing degree L balance and voltage fluctuation V van Optimize for multiple objectives.
[0146] Objective function:
[0147]
[0148] Where λ1 and λ2 are weighting factors, We assign a health score to the i-th path, with the objective of minimizing the combined cost of all objectives.
[0149] 2.4 Communication and Power Joint Optimization Module
[0150] The communication and power joint optimization module achieves coordinated optimization of communication frequency bands and power transmission paths through a multi-objective joint optimization strategy, ensuring that the two can support each other and dynamically adjust in complex environments.
[0151] Working principle: The communication and power joint optimization module adopts a multi-objective optimization algorithm (including MOEA / D) based on the Pareto frontier. It makes joint decisions based on communication signal quality, power transmission loss and system stability, and selects the globally optimal frequency band and path combination strategy.
[0152] Technical details:
[0153] Multi-objective optimization submodule:
[0154] The NSGA-II algorithm is used to transform the multi-objective problem of communication and power into multiple scalar subproblems for solution.
[0155] Joint Strategy Decision Submodule:
[0156] Based on the Pareto frontier theory, a comprehensive evaluation of joint strategies for communication and power is conducted, and the optimal joint strategy scheme is output.
[0157] 2.5 Linkage Control Module
[0158] When an anomaly occurs in the communication or power system, the linkage control module dynamically adjusts the frequency band and power dispatch strategy through real-time linkage control to ensure the continuity and stability of the system.
[0159] 2.6 Redundancy Switching and Fault Recovery Module
[0160] The redundancy switching and fault recovery module manages redundant frequency bands and the backup power path library to quickly switch to the backup plan in the event of a system failure, and completes fault switching and recovery within 10ms using a dynamic programming algorithm.
[0161] 3. Advantages of the system
[0162] The intelligent frequency selection system of this invention possesses high adaptability and the ability to handle complex scenarios, enabling efficient and continuous optimization of communication and power transmission in various complex environments. Its innovation is mainly reflected in multi-objective adaptive optimization, dynamic frequency band selection based on reinforcement learning, and multi-scenario linkage control strategies.
[0163] 4. Specific application scenarios and implementation results
[0164] This system can be widely applied to various complex vehicle-mounted communication and power systems, including electric transport fleets and high-speed train communication systems. It can significantly improve the communication quality of vehicle-mounted radios and the reliability of power transmission.
[0165] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.
Claims
1. An intelligent frequency selection system for vehicle-mounted VHF radios, characterized in that, The system includes the following modules: The multi-scenario environment perception module is used to collect information on the current environment's communication frequency band status, power load status, and geographical environment through various sensors, and to classify the current scenario and predict the dynamic environmental status. The intelligent frequency selection module is used to select frequency bands and switch dynamically based on the scene classification results and frequency band health information provided by the multi-scene environment perception module and an adaptive frequency selection algorithm. The power transmission optimization module is used to dynamically adjust the power transmission path based on the health assessment of power transmission lines and load distribution information, so as to achieve the optimal power dispatch strategy. The communication and power joint optimization module is used to achieve coordinated optimization of communication frequency bands and power transmission paths through multi-objective optimization algorithms when communication frequency bands are interfered with or power path failures occur. The linkage control module is used to coordinate and adjust the frequency band and power dispatch through real-time linkage strategies when there are abnormalities in the communication frequency band or power transmission path. The redundancy switching and fault recovery module is used to activate the redundant frequency band and backup path library and perform rapid fault recovery and switching when communication frequency band or power path failure occurs.
2. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, The multi-scene environment perception module further includes: The data acquisition submodule is used to collect various environmental characteristic data, including communication frequency band characteristic data (including signal strength, signal-to-noise ratio, and frequency band occupancy status), power load characteristic data (including line voltage, current, load density, and line impedance), and environmental status characteristic data (including geographic information, terrain perception, and road status). The scene recognition submodule is used to extract features from the collected data and identify the current scene using a machine learning-based classification model to generate scene labels. The dynamic environment prediction submodule is used to make short-term (1-5 seconds) predictions of future environmental conditions using a time-series prediction model and output environmental condition warning signals. The environmental health assessment submodule is used to assess the health of each frequency band, load path, and environmental characteristics, and generate an environmental health index (a score between 0 and 1).
3. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, The intelligent frequency selection module further includes: The frequency band health assessment submodule is used to comprehensively assess the signal strength, signal-to-noise ratio, bandwidth utilization, and interference status of all available communication frequency bands based on fuzzy logic algorithms, and to calculate the health score of each frequency band. The adaptive frequency selection submodule is used to select the optimal frequency band based on reinforcement learning algorithms (including DQN algorithm) and the current scene label and frequency band health score; The frequency band switching control submodule is used to detect when the signal quality of the current frequency band deteriorates or interference increases. It then uses an interference source identification and prediction model to determine the type of interference and initiate a frequency band switching strategy. The frequency band switching smoothing submodule is used to perform short-term parallel transmission between the old and new frequency bands during frequency band switching using a gradual switching strategy, ensuring the continuity of data transmission and communication quality.
4. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, The power transmission optimization module further includes: The power path health assessment submodule is used to calculate the health of each power transmission path in real time based on voltage stability, load density, and current fluctuation characteristic parameters, and generate a health score. The dynamic load scheduling submodule is used to dynamically adjust the power transmission strategy based on the health of the current power transmission path and the load distribution information, using a multi-objective optimization algorithm. The power path selection and switching submodule is used to activate the load distribution and switching strategy of the backup power path when the health score of a power transmission path is detected to be lower than a preset threshold.
5. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, The joint optimization module for communication and power further includes: The multi-objective optimization submodule is used to perform joint optimization based on multiple objectives such as communication signal quality, power transmission health, and system operation stability, using multi-objective optimization algorithms (including MOEA / D). The joint strategy decision-making submodule is used to select the optimal combination strategy of communication frequency band and power path based on Pareto front theory, and to adjust the global scheduling scheme of the system in real time.
6. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, The linkage control module further includes: The frequency band and power path linkage submodule is used to adjust the load distribution strategy of the power path when interference occurs in the communication frequency band, and to prioritize the communication frequency band with the best signal quality when the power path fails. The dynamic recovery and adjustment submodule is used to adjust the linkage strategy between communication and power according to the dynamic changes in real-time environmental conditions and load requirements.
7. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, The redundancy switching and fault recovery module further includes: The redundant frequency band and path library management submodule is used to establish multiple redundant frequency bands and power path libraries, and to dynamically update them according to real-time environmental conditions and path health. The fast fault recovery submodule is used to activate the fast fault recovery strategy when a communication frequency band or power path fault is detected. It selects the backup frequency band or path with the highest health and completes the fault switching and system recovery within 10ms.
8. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, The system also includes an adaptive weight adjustment module, which dynamically adjusts the weight values of different optimization objectives based on the current environmental state and the priority of the optimization objectives, thereby achieving adaptive optimization trade-offs.
9. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, The adaptive frequency selection submodule in the intelligent frequency selection module further employs a multi-level optimization algorithm, including: The global search hierarchy is used to perform a global band search across all available communication bands and select the potentially optimal band. Local fine-tuning hierarchy is used to fine-tune local parameters in the globally optimal frequency band, thereby improving the utilization rate of communication frequency bands and signal quality.
10. The intelligent frequency selection system for vehicle-mounted VHF radios according to claim 1, characterized in that, All modules integrated in the system can be uniformly scheduled through a central controller, and data interaction and collaborative work between multiple modules can be realized based on dynamic perception and adaptive optimization strategies. The central controller further includes: The data storage module is used to store environmental data, historical frequency band usage data, and power transmission status information; The decision engine module is used to make comprehensive decisions on the current strategy based on a multi-objective optimization model, and output the optimal communication frequency band and power path strategy.