12 results about "Green vehicle" patented technology

Aiming at the problem of time-dependent multi-target green vehicle path optimization, the invention designs a space-time attenuation factor-driven urban logistics low-carbon robust optimization method, takes the total vehicle distribution time and carbon emission as optimization targets, and adopts double-layer ant colony pheromones to guide ant colony search, so that the optimal path optimization is realized. The adaptive capacity of ants in a high-disturbance uncertain environment is improved, the convergence of solutions is enhanced, more solution sets balancing robustness and optimality are excavated through solution robustness evaluation and a feedback mechanism thereof, the diversity of optimal solutions is improved, an optimal vehicle path robust optimization scheme is obtained, the carbon emission of urban road network distribution is reduced, and the urban road network distribution efficiency is improved. And the distribution efficiency of logistics is improved.

This invention belongs to the field of intelligent transportation technology, specifically relating to a method for detecting abnormal transportation status of green channel vehicles based on highway OD data. This invention overcomes the limitations of traditional manual spot checks and simple weighing comparisons, which can only address explicit problems, through the coordinated operation of data acquisition, origin anomaly judgment, weight loss anomaly judgment, and comprehensive early warning. It accurately identifies non-overweight transportation anomalies with strong concealment, such as substandard loading rates, mixed loading of light and heavy goods to increase weight, and false declaration of goods, filling a gap in existing technology in this field. Based on big data such as highway OD, this invention conducts intelligent screening from the macro-level patterns of transportation behavior, significantly reducing the hardware investment and operating costs of green channel policy supervision. At the same time, it overcomes the drawbacks of low efficiency, narrow coverage, and strong subjectivity of manual detection, achieving automated and comprehensive screening of the transportation status of green channel vehicles, greatly improving regulatory efficiency and coverage.

This invention relates to onboard hot-water-storage-based power systems for vehicles. In this system, sufficiently high-temperature water is stored onboard an automotive vehicle, and thermal energy it contains is converted into mechanical work via a heat engine to propel the vehicle without combustion. Hot-water-powered vehicles offer a truly renewable and clean transportation solution and represent a nature-based strategy (MBS) for addressing global warming. Beyond conventional road vehicles, the hot-water power system is also applicable to off-road and specialized platforms, including agricultural machinery, short-haul marine vessels, construction and mining equipment, and rail transportation. Given that the transportation sector is a major contributor to global greenhouse gas emissions, hot-water-based vehicles are envisioned as a transformative path toward long-term sustainability, with substantial positive impacts on both the environment and the broader transportation industry.

The invention discloses a time-varying green vehicle multi-target path planning method based on iterative local search, and the method comprises the steps: 1, building a vehicle logistics-oriented time-varying green vehicle multi-target path planning model for the time-varying path planning of a fuel vehicle, and enabling the model to be used for describing the correlation condition of time-varying speed, vehicle load and fuel consumption; 2, constructing a multi-target time-varying green vehicle path planning model in combination with a time-varying driving time model and a load-speed-distance coupled fuel consumption model; and 3, solving a path planning model by using a heuristic algorithm based on iterative local search to obtain a path planning scheme. According to the method, a distribution path scheme of time-varying speed characteristics and multi-target tradeoff can be optimized, and the problem of collaborative optimization of vehicle paths and fuel consumption in a time-varying traffic environment can be solved, so that the total distance, the transportation time and the fuel consumption can be reduced, and emission is reduced.

This invention relates to onboard hot-water-storage-based power systems for vehicles. In this system, sufficiently high-temperature water is stored onboard an automotive vehicle, and thermal energy it contains is converted into mechanical work via a heat engine to propel the vehicle without combustion. Hot-water-powered vehicles offer a truly renewable and clean transportation solution and represent a nature-based strategy (MBS) for addressing global warming. Beyond conventional road vehicles, the hot-water power system is also applicable to off-road and specialized platforms, including agricultural machinery, short-haul marine vessels, construction and mining equipment, and rail transportation. Given that the transportation sector is a major contributor to global greenhouse gas emissions, hot-water-based vehicles are envisioned as a transformative path toward long-term sustainability, with substantial positive impacts on both the environment and the broader transportation industry.

The utility model relates to the technical field of vehicle-mounted watering, and discloses a greening vehicle-mounted watering device which comprises a carrying bottom plate and a water tank, a water adding opening is formed in the left side of the top of the water tank, open grooves are formed in the two sides of a water level column, a floating ball is assembled in the water level column, and an infrared sensor is assembled at the top end in the water level column. Light-transmitting glass is installed at the position, close to the upper portion, in the water level column. The water tank, the pump body and the like are assembled above the carrying bottom plate, then the carrying bottom plate is assembled on the vehicle through the bolts so as to move along with movement of the vehicle, the positioning seat is fixed to the left side of the top of the carrying bottom plate, and therefore the water tank can be placed in the positioning seat; therefore, the sponge cushion is adopted between the positioning seat and the water tank for contact buffering protection, so that the shaking problem of the water tank is reduced when a vehicle runs, and the overall stability is better improved in the working process.

The invention discloses a low-power-consumption identity recognition system and method for a bicycle wireless transmission, and the method comprises the steps: a wake-up module detects at least one operation parameter of a bicycle to determine the actual operation state of the bicycle, and selectively activates or closes an identity recognition module and a control module to achieve a low-power-consumption state; the identity recognition module obtains identity information of a user, recognizes the identity of the user and sends out a recognition signal; the control module receives an identification signal sent by the identity identification module and sends a control signal according to an analysis result; according to the low-power-consumption identity recognition system, the low-power-consumption identity recognition technology is adopted, the energy consumption of the system is effectively reduced, the service life of the storage battery is prolonged, and the high requirement for energy efficiency when a bicycle serves as a green vehicle is met. Through the identity recognition system, only an authorized user is allowed to operate the wireless transmission, unauthorized use and misoperation are prevented, and the safety and anti-theft performance of the bicycle are greatly improved.

The application belongs to the field of intelligent logistics, and specifically discloses a green vehicle path planning method and system for a logistics site, which comprises the following steps: acquiring path planning basic data; based on the basic data, constructing a quantitative model for dynamically calculating carbon emissions based on vehicle driving time, speed and load, setting constraint conditions for path planning based on logistics information, and establishing a multi-objective function including a driving distance target and a carbon emission target obtained based on the quantitative model; using a tent mapping to generate an initial population of a starling optimization algorithm, with each starling individual corresponding to a path planning solution; using an improved starling optimization algorithm with a polynomial mutation disturbance strategy to iteratively solve the multi-objective function under the constraint conditions, and outputting an optimized path planning solution. Through the application, the dynamic and accurate calculation of carbon emissions of vehicles under different load conditions and driving speeds is realized, and a more low-carbon and green vehicle driving path for a logistics site is planned.

The application relates to the technical field of intelligent transportation, and discloses a green vehicle auditing model and method based on multi-dimensional feature cross analysis, which comprises a feature enhancement module, a multi-dimensional feature vector construction module, a comprehensive scoring module, a weight training module and a risk grading module. The method corresponds to the model. According to the application, by constructing a five-dimensional feature vector of time, space, behavior, load and history, relying on core algorithms such as cosine similarity algorithm for quantifying time period matching degree and exponential decay function for mapping path deviation degree, cross analysis of multi-dimensional features is realized, and with the aid of XGBoost machine learning, dynamic optimization of feature weight and risk grading threshold is realized, hidden correlations between unreasonable seasons and path deviations and other features are captured through a self-adaptive coupling module, and the weight of recent abnormal behavior is strengthened by using time decay credit points, so that the misjudgment rate and the missed judgment rate are effectively reduced, and the problem of missed detection of composite risks in traditional single-dimensional detection is solved.

The application provides a high-speed green-pass vehicle escape fee identification method, system and medium. The method comprises the following steps: obtaining vehicle pass record data of a green-pass lane, preprocessing the vehicle pass record data, obtaining optimized vehicle pass record data, constructing a green-pass vehicle escape fee identification rule set, performing green-pass vehicle escape fee identification, obtaining a suspected escape fee vehicle state, if the suspected escape fee vehicle state is obtained, analyzing and processing the suspected escape fee vehicle state by a preset escape fee confidence processing method, obtaining an escape fee confidence, and finally performing threshold comparison, if the escape fee confidence is less than a preset escape fee confidence threshold, activating manual review, if the escape fee confidence is greater than or equal to the preset escape fee confidence threshold, generating a green-pass vehicle escape fee identification report through a preset green-pass escape fee identification template. The application realizes accurate identification of high-speed green-pass vehicle escape fee by constructing image data analysis and core mining, performing multi-dimensional analysis on vehicle pass record data of a green-pass lane, and accurately identifying various escape fee behaviors.

The invention relates to a method for rapidly checking a green channel vehicle based on an AI model, and relates to the technical field of computer processing, and the method comprises the following steps: S1, in the loading operation process of the green channel vehicle, starting a vehicle-mounted intelligent terminal to carry out whole-course audio and video data collection, the collected first data set is encrypted and then uploaded to the cloud server in real time; s2, generating a second data set according to the planned driving route of the reported green channel vehicle, and associating the second data set with the first data set to obtain associated loading data; and S3, at the first toll station node where the green channel vehicle passes, based on the associated loading data, performing automatic verification on the compliance of the loading operation. According to the method, efficient inspection of the green channel vehicles is realized, the passing verification time is remarkably shortened, the operation management efficiency of the highway toll station is improved, the economic benefits of transportation enterprises and truck drivers are effectively improved, and the method has good industrial application value.

1. The name of the design product: electronic device with high-speed green pass vehicle management graphical user interface. 2. The use of the design product: the design product is used for an electronic device. 3. The design points of the design product: the interface content and layout of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: interface change state diagram 1. 5. Other views are conventional designs, and other views are omitted. 6. The use of the graphical user interface: to provide intuitive, accurate and efficient high-speed green pass inspection, judgment, analysis and historical query functions for high-speed green pass management personnel. 7. The human-computer interaction mode of the graphical user interface: the main view is the homepage of the system software for high-speed green pass vehicle inspection and judgment. After entering "username", "password" and "scheduling personnel" in the main view and clicking "login confirmation", the interface change state diagram 1 can be entered. On the basis of the interface change state diagram 1, the license plate information is input or the scanning icon on the right side of the green license plate is clicked to scan the license plate, and after filling in the corresponding information below and clicking "submit", the interface change state diagram 2 can be entered. On the basis of the interface change state diagram 2, the page is slid down to enter the interface change state diagram 3. On the basis of the interface change state diagram 3, the page is slid down to enter the interface change state diagram 4.