A mobile battery replacement system applied to a new energy vehicle

Abstract

The application relates to a mobile battery replacement system applied to a new energy automobile, which comprises a fixed charging station, a tractor and a mobile battery replacement transfer vehicle. The tractor comprises a tractor head and a battery storage unit. The tractor head is used for transporting the battery storage unit back and forth between the fixed charging station and the mobile battery replacement transfer vehicle. The battery storage unit comprises a container body, a battery base, a battery state detection module and a fire-fighting emergency system. The battery base is arranged in the container body and is used for fastening a battery and providing a charging and communication interface between the battery base and the battery. The battery state detection module is in communication connection with the battery base. The application can provide more flexible battery replacement services. The tractor head can be separated from the container, the battery container can be parked at the fixed charging station, the tractor head can be combined with other full-battery containers, and the tractor head can continue to work.

Description

Technical Field

[0001] This invention relates to the field of new energy vehicle technology, and in particular to a mobile battery swapping system for new energy vehicles. Background Technology

[0002] In response to the national call for energy conservation and emission reduction, vehicles and equipment powered by fuel have been gradually replaced by electric vehicles and equipment in recent years. However, electric equipment is subject to various limitations in terms of range, charging efficiency, and service life compared to fuel-powered equipment. To address these issues, battery-swapping vehicles have emerged in the market, providing direct battery swapping for electric equipment and enabling rapid recharging.

[0003] In existing technologies, due to the large weight of the battery pack, a ground support mechanism needs to be deployed before the battery swapping vehicle can operate. Furthermore, because the vehicle needs to maintain the same level as the vehicle being swapped, a significant amount of time is required for ground leveling. Often, the battery swapping vehicle has to wait up to 30 minutes before the swapping operation can begin. This results in prolonged waiting and preparation time, wasted time, low swapping efficiency, and a poor swapping experience. Summary of the Invention

[0004] In view of the above problems, the present invention provides a mobile battery swapping system for new energy vehicles, which not only provides more flexible battery swapping services, but also allows the tractor unit to be separated from the container, leaving the battery container at a fixed charging station, and the tractor unit to be combined with other fully charged battery containers to continue working.

[0005] To achieve the above and other related objectives, the present invention provides the following technical solution: A mobile battery swapping system for new energy vehicles includes a fixed charging station, a tractor, and a mobile battery swapping transfer vehicle. The tractor unit includes a tractor head and a battery storage unit. The tractor head is used to transport the battery storage unit back and forth between the fixed charging station and the mobile battery swapping transfer vehicle. The battery storage unit includes a container body, a battery base, a battery status detection module, and a fire emergency system. The battery base is located inside the container body. The battery base is used to secure the battery and provide a charging and communication interface with the battery. The battery status detection module is communicatively connected to the battery base to monitor the battery power or fault status in real time. The fire emergency system is used to deal with the fire in time in the event of a fire to avoid greater damage and loss. The mobile battery swapping transfer vehicle includes a lifting assembly, a flatbed semi-trailer, flatbed hydraulic outriggers, a mobile battery swapping station control assembly, a high-precision positioning module, and a parking guidance module. The lifting assembly is used to lift the battery pack and can move laterally and longitudinally, extending to the left and right sides. The flatbed semi-trailer serves as the carrier for the lifting assembly and the mobile battery swapping station control assembly. The parking guidance module uses neural network algorithms and PRM algorithms to guide the tractor and battery swapping vehicle to park at designated locations for battery swapping operations.

[0006] Furthermore, the step of using neural network algorithms and PRM algorithms to guide the tractor and battery swapping vehicle to stop at the designated location for battery swapping operations includes: U1. Acquire 2D BEV data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle, and use the Pearson coefficient algorithm to calculate the relevant distance between the two vehicles, and output the relevant distance data information between the tractor and the battery swapping vehicle, the relevant distance data information between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data information between the battery swapping vehicle and the mobile battery swapping transfer vehicle. U2. Divide the relevant distance data between the tractor and the battery swapping vehicle, the relevant distance data between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data between the battery swapping vehicle and the mobile battery swapping transfer vehicle into a training dataset and a test training dataset. Input the training dataset into the neural network model for training and learning, and output the trained neural network model. U3. Input the test training dataset into the trained neural network model, perform vehicle pose prediction on the tractor, battery swapping vehicle and mobile battery swapping transfer vehicle, and output the predicted tractor pose data, the predicted battery swapping vehicle pose data and the predicted mobile battery swapping transfer vehicle pose data. U4. Based on the predicted tractor pose data, the predicted battery swapping vehicle pose data, and the predicted mobile battery swapping transfer vehicle pose data, the PRM algorithm is used to plan the vehicle trajectory, and the trajectory planning data of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle are output.

[0007] Furthermore, in step U4, if the predicted tractor pose data remains unchanged, the trajectories of the battery swapping vehicle and the mobile battery swapping transfer vehicle are planned according to the PRM algorithm; if the predicted battery swapping vehicle pose data remains unchanged, the trajectories of the mobile battery swapping transfer vehicle and the tractor are planned according to the PRM algorithm; if the predicted mobile battery swapping transfer vehicle pose data remains unchanged, the trajectories of the tractor and the battery swapping vehicle are planned according to the PRM algorithm.

[0008] Furthermore, in step U4, if the predicted tractor pose data and the predicted battery swapping vehicle pose data remain unchanged, the trajectory of the mobile battery swapping transfer vehicle is planned according to the PRM algorithm.

[0009] Furthermore, in step U1, the calculation of the relevant distance between the two vehicles using the Pearson coefficient algorithm includes: U11. Acquire 2D BEV data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle; establish a unified coordinate system; and output the boundary coordinate point data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle. U12. Based on the boundary coordinate point data of the tractor, the boundary coordinate point data of the battery swapping vehicle, and the boundary coordinate point data of the mobile battery swapping transfer vehicle, establish a distance correlation coefficient function L for any two vehicles. xy , , Where x and y are the boundary coordinates of any two vehicles, COV(x,y) is the covariance of x and y, D(x) is the variance of x, and D(y) is the variance of y. U13. Based on the distance correlation coefficient function L of any two vehicles xy Establish the correlation distance function Q between any two vehicles. xy , Q xy =1-L xy , Among them, L xy Let be the distance correlation coefficient function between any two vehicles, and obtain the relevant distance data between the tractor and the battery swapping vehicle, the relevant distance data between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data between the battery swapping vehicle and the mobile battery swapping transfer vehicle.

[0010] Furthermore, the mobile battery swapping station control component is used to provide power to the mobile battery swapping hoisting vehicle and control the operation of the mobile battery swapping hoisting mechanism.

[0011] Furthermore, the hydraulic support legs of the flatbed truck are used for electrically controlled telescopic leveling of the vehicle, supporting the vehicle body to prevent tipping.

[0012] Furthermore, the fixed charging station is used to charge and replenish the batteries replaced by new energy vehicles, achieving centralized management and distribution of batteries.

[0013] Furthermore, the high-precision positioning module is connected to the parking guidance module to provide vehicle location data information.

[0014] Furthermore, the fire emergency system includes a monitoring module and an early warning module. The monitoring module is connected to the early warning module, and the early warning module is used to make threshold judgments based on the monitoring data provided by the monitoring module and issue voice broadcast prompts.

[0015] The present invention has the following positive effects: 1. This invention uses neural network algorithms and PRM algorithms to guide the tractor and battery swapping vehicle to stop at designated locations for battery swapping operations. This not only optimizes the vehicle trajectory planning but also increases the efficiency of battery swapping, further improving the convenience of mobile battery swapping.

[0016] 2. The mobile battery swapping crane of the present invention is easy to deploy, does not require building approval, can provide more flexible battery swapping services, and the mobile battery swapping station can use hydraulic outriggers to level the ground, which can cope with various different usage scenarios.

[0017] 3. After the tractor of the present invention transports the battery container to a fixed charging station or a mobile battery swapping crane, the tractor head can be separated from the container, leaving the battery container at the fixed charging station. The tractor head can be combined with other fully charged battery containers to continue working. The battery base in the battery container can be directly connected to the power supply equipment of the fixed charging station. The charging work of each battery is intelligently allocated according to the battery monitoring module. The fire emergency system can prevent the risk of fire during charging and battery swapping. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the mobile battery swapping operation of the present invention; Figure 2 This is a flowchart illustrating the use of neural network algorithms and PRM algorithms in this invention to guide the tractor and battery swapping vehicle to stop at a designated location for battery swapping operations. Detailed Implementation

[0019] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0020] Example 1: As Figure 1 As shown, a mobile battery swapping system for new energy vehicles includes a fixed charging station, a tractor, and a mobile battery swapping transfer vehicle. The tractor unit includes a tractor head and a battery storage unit. The tractor head is used to transport the battery storage unit back and forth between the fixed charging station and the mobile battery swapping transfer vehicle. The battery storage unit includes a container body, a battery base, a battery status detection module, and a fire emergency system. The battery base is located inside the container body. The battery base is used to secure the battery and provide a charging and communication interface with the battery. The battery status detection module is communicatively connected to the battery base to monitor the battery power or fault status in real time. The fire emergency system is used to deal with the fire in time in the event of a fire to avoid greater damage and loss. The mobile battery swapping transfer vehicle includes a lifting assembly, a flatbed semi-trailer, flatbed hydraulic outriggers, a mobile battery swapping station control assembly, a high-precision positioning module, and a parking guidance module. The lifting assembly is used to lift the battery pack and can move laterally and longitudinally, extending to the left and right sides. The flatbed semi-trailer serves as the carrier for the lifting assembly and the mobile battery swapping station control assembly. The parking guidance module uses neural network algorithms and PRM algorithms to guide the tractor and battery swapping vehicle to park at designated locations for battery swapping operations.

[0021] In this embodiment, as Figure 2 As shown, the steps of using neural network algorithms and PRM algorithms to guide the tractor and battery swapping vehicle to stop at the designated location for battery swapping operations include: U1. Acquire 2D BEV data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle, and use the Pearson coefficient algorithm to calculate the relevant distance between the two vehicles, and output the relevant distance data information between the tractor and the battery swapping vehicle, the relevant distance data information between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data information between the battery swapping vehicle and the mobile battery swapping transfer vehicle. U2. Divide the relevant distance data between the tractor and the battery swapping vehicle, the relevant distance data between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data between the battery swapping vehicle and the mobile battery swapping transfer vehicle into a training dataset and a test training dataset. Input the training dataset into the neural network model for training and learning, and output the trained neural network model. U3. Input the test training dataset into the trained neural network model, perform vehicle pose prediction on the tractor, battery swapping vehicle and mobile battery swapping transfer vehicle, and output the predicted tractor pose data, the predicted battery swapping vehicle pose data and the predicted mobile battery swapping transfer vehicle pose data. U4. Based on the predicted tractor pose data, the predicted battery swapping vehicle pose data, and the predicted mobile battery swapping transfer vehicle pose data, the PRM algorithm is used to plan the vehicle trajectory, and the trajectory planning data of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle are output.

[0022] In this embodiment, in step U4, if the predicted tractor pose data remains unchanged, the trajectories of the battery swapping vehicle and the mobile battery swapping transfer vehicle are planned according to the PRM algorithm; if the predicted battery swapping vehicle pose data remains unchanged, the trajectories of the mobile battery swapping transfer vehicle and the tractor are planned according to the PRM algorithm; if the predicted mobile battery swapping transfer vehicle pose data remains unchanged, the trajectories of the tractor and the battery swapping vehicle are planned according to the PRM algorithm.

[0023] In this embodiment, in step U4, if the predicted tractor pose data and the predicted battery swapping vehicle pose data remain unchanged, the trajectory of the mobile battery swapping transfer vehicle is planned according to the PRM algorithm.

[0024] Example 2: Based on the mobile battery swapping system for new energy vehicles in Example 1, the present invention will be further described and explained below.

[0025] like Figure 1 As shown, a mobile battery swapping system for new energy vehicles includes a fixed charging station, a tractor, and a mobile battery swapping transfer vehicle. The tractor unit includes a tractor head and a battery storage unit. The tractor head is used to transport the battery storage unit back and forth between the fixed charging station and the mobile battery swapping transfer vehicle. The battery storage unit includes a container body, a battery base, a battery status detection module, and a fire emergency system. The battery base is located inside the container body. The battery base is used to secure the battery and provide a charging and communication interface with the battery. The battery status detection module is communicatively connected to the battery base to monitor the battery power or fault status in real time. The fire emergency system is used to deal with the fire in time in the event of a fire to avoid greater damage and loss. The mobile battery swapping transfer vehicle includes a lifting assembly, a flatbed semi-trailer, flatbed hydraulic outriggers, a mobile battery swapping station control assembly, a high-precision positioning module, and a parking guidance module. The lifting assembly is used to lift the battery pack and can move laterally and longitudinally, extending to the left and right sides. The flatbed semi-trailer serves as the carrier for the lifting assembly and the mobile battery swapping station control assembly. The parking guidance module uses neural network algorithms and PRM algorithms to guide the tractor and battery swapping vehicle to park at designated locations for battery swapping operations.

[0026] In this embodiment, step U1, which involves using the Pearson coefficient algorithm to calculate the relevant distance between the two vehicles, includes: U11. Acquire 2D BEV data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle; establish a unified coordinate system; and output the boundary coordinate point data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle. U12. Based on the boundary coordinate point data of the tractor, the boundary coordinate point data of the battery swapping vehicle, and the boundary coordinate point data of the mobile battery swapping transfer vehicle, establish a distance correlation coefficient function L for any two vehicles. xy , , Where x and y are the boundary coordinates of any two vehicles, COV(x,y) is the covariance of x and y, D(x) is the variance of x, and D(y) is the variance of y. U13. Based on the distance correlation coefficient function L of any two vehicles xy Establish the correlation distance function Q between any two vehicles. xy , Q xy =1-L xy , Among them, L xy Let be the distance correlation coefficient function between any two vehicles, and obtain the relevant distance data between the tractor and the battery swapping vehicle, the relevant distance data between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data between the battery swapping vehicle and the mobile battery swapping transfer vehicle.

[0027] In this embodiment, the mobile battery swapping station control component is used to provide power to the mobile battery swapping hoisting vehicle and control the operation of the mobile battery swapping hoisting mechanism.

[0028] In this embodiment, the hydraulic support legs of the flatbed truck are used for electrically controlled telescopic leveling of the vehicle, supporting the vehicle body to prevent it from tipping over.

[0029] In this embodiment, the fixed charging station is used to charge and replenish the batteries replaced by new energy vehicles, so as to achieve centralized management and distribution of batteries.

[0030] In this embodiment, the high-precision positioning module is connected to the parking guidance module to provide vehicle location data information.

[0031] In this embodiment, the fire emergency system includes a monitoring module and an early warning module. The monitoring module is connected to the early warning module, and the early warning module is used to determine a threshold based on the monitoring data provided by the monitoring module and issue a voice broadcast prompt.

[0032] In summary, this invention not only provides a more flexible battery swapping service, but also allows the tractor unit to be separated from the container, leaving the battery container at a fixed charging station. The tractor unit can then be combined with other fully charged battery containers to continue operating.

[0033] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A mobile battery swapping system for new energy vehicles, comprising a fixed charging station, a tractor, and a mobile battery swapping transfer vehicle, characterized in that: The tractor unit includes a tractor head and a battery storage unit. The tractor head is used to transport the battery storage unit back and forth between the fixed charging station and the mobile battery swapping transfer vehicle. The battery storage unit includes a container body, a battery base, a battery status detection module, and a fire emergency system. The battery base is located inside the container body. The battery base is used to secure the battery and provide a charging and communication interface with the battery. The battery status detection module is communicatively connected to the battery base to monitor the battery power or fault status in real time. The fire emergency system is used to deal with the fire in time in the event of a fire to avoid greater damage and loss. The mobile battery swapping transfer vehicle includes a lifting assembly, a flatbed semi-trailer, flatbed hydraulic outriggers, a mobile battery swapping station control assembly, a high-precision positioning module, and a parking guidance module. The lifting assembly is used to lift the battery pack and can move laterally and longitudinally, extending to the left and right sides. The flatbed semi-trailer serves as the carrier for the lifting assembly and the mobile battery swapping station control assembly. The parking guidance module uses neural network algorithms and PRM algorithms to guide the tractor and battery swapping vehicle to park at a designated location for battery swapping operations. The steps of using neural network algorithms and PRM algorithms to guide the tractor and battery swapping vehicle to stop at the designated location for battery swapping operations include: U1. Acquire 2D BEV data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle, and use the Pearson coefficient algorithm to calculate the relevant distance between the two vehicles, and output the relevant distance data information between the tractor and the battery swapping vehicle, the relevant distance data information between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data information between the battery swapping vehicle and the mobile battery swapping transfer vehicle. U2. Divide the relevant distance data between the tractor and the battery swapping vehicle, the relevant distance data between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data between the battery swapping vehicle and the mobile battery swapping transfer vehicle into a training dataset and a test training dataset. Input the training dataset into the neural network model for training and learning, and output the trained neural network model. U3. Input the test training dataset into the trained neural network model, perform vehicle pose prediction on the tractor, battery swapping vehicle and mobile battery swapping transfer vehicle, and output the predicted tractor pose data, the predicted battery swapping vehicle pose data and the predicted mobile battery swapping transfer vehicle pose data. U4. Based on the predicted tractor pose data, the predicted battery swapping vehicle pose data, and the predicted mobile battery swapping transfer vehicle pose data, the PRM algorithm is used to plan the vehicle trajectory, and the trajectory planning data of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle are output.

2. The mobile battery swapping system for new energy vehicles according to claim 1, characterized in that, In step U4, if the predicted tractor pose data remains unchanged, the trajectories of the battery swapping vehicle and the mobile battery swapping transfer vehicle are planned according to the PRM algorithm. If the predicted battery swapping vehicle pose data remains unchanged, the trajectories of the mobile battery swapping transfer vehicle and the tractor are planned according to the PRM algorithm. If the predicted mobile battery swapping transfer vehicle pose data remains unchanged, the trajectories of the tractor and the battery swapping vehicle are planned according to the PRM algorithm.

3. The mobile battery swapping system for new energy vehicles according to claim 1, characterized in that, In step U4, if the predicted tractor pose data and the predicted battery swapping vehicle pose data remain unchanged, the trajectory of the mobile battery swapping transfer vehicle is planned according to the PRM algorithm.

4. The mobile battery swapping system for new energy vehicles according to claim 1, characterized in that, In step U1, the calculation of the relevant distance between the two vehicles using the Pearson coefficient algorithm includes: U11. Acquire 2D BEV data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle; establish a unified coordinate system; and output the boundary coordinate point data information of the tractor, the battery swapping vehicle, and the mobile battery swapping transfer vehicle. U12. Based on the boundary coordinate point data of the tractor, the boundary coordinate point data of the battery swapping vehicle, and the boundary coordinate point data of the mobile battery swapping transfer vehicle, establish a distance correlation coefficient function L for any two vehicles. xy , ， Where x and y are the boundary coordinates of any two vehicles, COV(x,y) is the covariance of x and y, D(x) is the variance of x, and D(y) is the variance of y. U13. Based on the distance correlation coefficient function L of any two vehicles xy Establish the correlation distance function Q between any two vehicles. xy , Q xy =1-L xy , Among them, L xy Let be the distance correlation coefficient function between any two vehicles, and obtain the relevant distance data between the tractor and the battery swapping vehicle, the relevant distance data between the tractor and the mobile battery swapping transfer vehicle, and the relevant distance data between the battery swapping vehicle and the mobile battery swapping transfer vehicle.

5. The mobile battery swapping system for new energy vehicles according to claim 1, characterized in that: The mobile battery swapping station control component is used to provide power to the mobile battery swapping hoisting vehicle and control the operation of the mobile battery swapping hoisting mechanism.

6. The mobile battery swapping system for new energy vehicles according to claim 1, characterized in that: The hydraulic support legs of the flatbed truck are used for electrically controlled telescopic leveling of the vehicle and to support the vehicle body to prevent it from tipping over.

7. The mobile battery swapping system for new energy vehicles according to claim 1, characterized in that: The fixed charging stations are used to charge and replenish the batteries replaced by new energy vehicles, enabling centralized management and distribution of batteries.

8. The mobile battery swapping system for new energy vehicles according to claim 1, characterized in that: The high-precision positioning module is connected to the parking guidance module and is used to provide vehicle location data information.

9. The mobile battery swapping system for new energy vehicles according to claim 1, characterized in that: The fire emergency system includes a monitoring module and an early warning module. The monitoring module is connected to the early warning module. The early warning module is used to determine a threshold based on the monitoring data provided by the monitoring module and issue a voice broadcast prompt.

Images