Extended-range electric mine truck energy consumption optimization management system and method

Abstract

The invention belongs to the technical field of electric vehicle energy consumption management, and provides a range-extended electric mine truck energy consumption optimization management system and method, and the system comprises a vehicle control unit, a power battery management system, a range extender controller, an engine, a generator, a drive motor and a gearbox. Wherein the vehicle control unit is respectively connected with the power battery management system, the range extender controller, the driving motor and the gearbox, and the range extender controller is respectively connected with the engine and the generator; according to the invention, the energy consumption condition of the extended-range electric mine truck can be monitored in real time, and the working mode of the range extender and the output power of the driving motor are optimized and managed according to the running state of the vehicle and the electric quantity state of the battery, so that the energy utilization rate is improved; and meanwhile, the working mode of the range extender and the output power of the driving motor are optimized and managed, so that the endurance mileage of the range-extended electric mine truck can be effectively improved, the charging frequency is reduced, and the operation efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric vehicle energy consumption management, and in particular to an energy consumption optimization management system and method for an extended-range electric mining truck. Background Art

[0002] With increasingly stringent environmental protection requirements and the intensification of the energy crisis, new energy vehicles have become the development trend of the automotive industry. As a new type of new energy vehicle, extended-range electric vehicles have the advantages of long driving range, high energy utilization, and low emissions, and have received widespread attention. Mining trucks are heavy vehicles used for mine transportation, with harsh working environments, large loads, and long mileage.

[0003] Traditional fuel mining trucks have problems such as high fuel consumption, high emissions, and high noise, which seriously affect the production efficiency and environmental quality of mines. As a new type of mining truck, the extended-range electric mining truck has the advantages of no pollution, low noise, and high efficiency, which can effectively solve the problems of traditional fuel mining trucks;

[0004] However, in the existing technology, the energy consumption management of extended-range electric mining trucks mainly relies on simple threshold control or manual intervention, which makes it difficult to achieve efficient coordination of power sources and optimization of energy consumption, resulting in low energy utilization and high operating costs.

[0005] To this end, those skilled in the art have proposed an energy consumption optimization management system and method for extended-range electric mining trucks to solve the problems raised by the background technology. Summary of the invention

[0006] In order to solve the above technical problems, the present invention provides an energy consumption optimization management system and method for extended-range electric mining trucks, so as to solve the problems that the energy consumption management of extended-range electric mining trucks in the prior art mainly relies on simple threshold control or manual intervention, which makes it difficult to achieve efficient coordination of power sources and optimization of energy consumption, resulting in low energy utilization and high operating costs.

[0007] An energy consumption optimization management system and method for an extended-range electric mining truck, comprising a vehicle controller, a power battery management system, a range extender controller, an engine, a generator, a drive motor and a gearbox;

[0008] Among them, the vehicle controller is respectively connected to the power battery management system, the range extender controller, the drive motor and the gearbox, and the range extender controller is respectively connected to the engine and the generator.

[0009] Preferably, the vehicle controller is used to control the working mode of the range extender and the output power of the drive motor according to the driving state of the vehicle and the power state of the battery; the vehicle controller is also used to predict the required power of the vehicle according to the driving route and road condition information of the vehicle, and control the working mode of the range extender and the output power of the drive motor according to the prediction result; the vehicle controller is also used to control the start and stop of the range extender according to the power state and health state of the battery to ensure the service life of the battery; the vehicle controller is also used to communicate with external devices to realize remote monitoring and fault diagnosis;

[0010] The power battery management system is used to monitor the battery power status and health status, and send the battery information to the vehicle controller; the vehicle controller is also used to communicate with external devices to achieve remote monitoring and fault diagnosis;

[0011] The range extender controller is used to control the working state of the engine and the generator to ensure that the output power of the range extender meets the needs of the vehicle; the range extender controller is also used to control the speed and torque of the engine according to the working state and load condition of the engine to ensure the working efficiency and reliability of the engine; the range extender controller is also used to control the output voltage and current of the generator according to the working state and load condition of the generator to ensure the working efficiency and reliability of the generator;

[0012] The engine is used to drive the generator to generate electricity;

[0013] The generator is used to charge the drive motor and the battery;

[0014] The drive motor is used to drive the vehicle; the drive motor is also used to recover energy during braking and store the recovered energy in the battery;

[0015] The gearbox is used to adjust the speed and torque of the drive motor; the gearbox is also used to automatically adjust the gear according to the driving state and road condition information of the vehicle to ensure the driving comfort and economy of the vehicle.

[0016] Preferably, the power battery management system specifically includes:

[0017] Power monitoring module, used to monitor the battery power, fuel generator status and vehicle operating parameters of the electric mining truck in real time;

[0018] The intelligent control module uses a preset algorithm to calculate the optimal power distribution strategy based on the data from the power monitoring module;

[0019] The power switching module realizes seamless switching between electric and fuel power sources according to the instructions of the intelligent control module;

[0020] The energy consumption statistics module records and analyzes the energy consumption data of mining cards and provides feedback for optimization strategies.

[0021] Preferably, the intelligent control module adopts a machine learning algorithm to continuously optimize the power distribution strategy based on historical energy consumption data.

[0022] Preferably, the power switching module has fault self-detection and emergency switching functions to ensure that the mining truck can still operate normally when any power source fails.

[0023] A method for optimizing energy consumption management of an extended-range electric mining truck comprises the following steps:

[0024] S1, the vehicle controller obtains the driving status of the vehicle and the power status of the battery;

[0025] S2, the vehicle controller controls the working mode of the range extender and the output power of the drive motor according to the driving state of the vehicle and the power state of the battery; step S2 also includes: the vehicle controller predicts the required power of the vehicle according to the driving route and road condition information of the vehicle, and controls the working mode of the range extender and the output power of the drive motor according to the prediction result; step S2 also includes: the vehicle controller controls the start and stop of the range extender according to the power state and health state of the battery to ensure the service life of the battery;

[0026] S3, the range extender controller controls the working state of the engine and the generator to ensure that the output power of the range extender meets the needs of the vehicle; step S3 also includes: the range extender controller controls the speed and torque of the engine according to the working state and load condition of the engine to ensure the working efficiency and reliability of the engine; step S3 also includes: the range extender controller controls the output voltage and current of the generator according to the working state and load condition of the generator to ensure the working efficiency and reliability of the generator;

[0027] S4, the driving motor drives the vehicle to travel, and the gearbox adjusts the speed and torque of the driving motor; step S4 also includes: the driving motor recovers energy during braking and stores the recovered energy in the battery; step S4 also includes: the gearbox automatically adjusts the gear according to the vehicle's driving state and road condition information to ensure the vehicle's driving comfort and economy.

[0028] Preferably, the vehicle controller communicates with external devices to achieve remote monitoring and fault diagnosis.

[0029] Preferably, the power battery management system performs balanced management on the batteries to ensure the consistency and reliability of the batteries.

[0030] A processor is configured to execute the above-mentioned energy consumption optimization management system for extended-range electric mining trucks.

[0031] A machine-readable storage medium stores instructions, which, when executed by a processor, configure the processor to execute the above-mentioned extended-range electric mining truck energy consumption optimization management system.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. Real-time monitoring and optimization management: The present invention can monitor the energy consumption of the extended-range electric mining truck in real time, and optimize the working mode of the range extender and the output power of the drive motor according to the driving status of the vehicle and the power status of the battery, so as to improve the energy utilization rate;

[0034] 2. Improve the cruising range: The present invention can effectively improve the cruising range of the extended-range electric mining truck, reduce the number of charging times, and improve operational efficiency by optimizing the working mode of the range extender and the output power of the drive motor;

[0035] 3. Reduce operating costs: The present invention can effectively reduce the operating costs of extended-range electric mining trucks and improve the economic benefits of mines; through real-time monitoring and optimization of energy consumption management, it can reduce energy waste and fuel consumption, while extending the service life of batteries and reducing maintenance costs;

[0036] 4. Improve reliability and safety: The present invention can effectively improve the reliability and safety of the extended-range electric mining truck by real-time monitoring and control of the working status of the range extender and the drive motor; at the same time, by real-time monitoring and management of the battery's charge state and health state, the battery's service life and safety can be guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a framework diagram of the energy consumption optimization management system for the extended-range electric mining truck of the present invention;

[0038] Figure 2 This is a connection diagram of the vehicle controller of the present invention with the power battery management system, the range extender controller, the drive motor and the gearbox;

[0039] Figure 3 The range extender controller of the present invention is connected to the engine and the generator respectively;

[0040] Figure 4 This is a framework diagram of the power battery management system of the present invention;

[0041] Figure 5 This is a flow chart of the energy consumption optimization management method of the extended-range electric mining truck of the present invention. DETAILED DESCRIPTION

[0042] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0043] As attached Figure 1 To Attachment Figure 5 As shown:

[0044] Embodiment: The present invention provides an energy consumption optimization management system for an extended-range electric mining truck, such as Figure 1 As shown, it includes vehicle controller, power battery management system, range extender controller, engine, generator, drive motor and gearbox;

[0045] The vehicle controller is respectively connected to the power battery management system, the range extender controller, the drive motor and the gearbox. Figure 2 As shown, the range extender controller is connected to the engine and the generator respectively, as shown in FIG. Figure 3 shown.

[0046] Furthermore, the vehicle controller is used to control the working mode of the range extender and the output power of the drive motor according to the driving state of the vehicle and the power state of the battery;

[0047] The power battery management system is used to monitor the battery power status and health status, and send the battery information to the vehicle controller;

[0048] The range extender controller is used to control the working state of the engine and the generator;

[0049] The engine is used to drive the generator to generate electricity;

[0050] The generator is used to charge the drive motor and the battery;

[0051] The driving motor is used to drive the vehicle;

[0052] The gearbox is used to adjust the rotation speed and torque of the drive motor.

[0053] Specifically, Figure 4 As shown, the power battery management system specifically includes:

[0054] Power monitoring module, used to monitor the battery power, fuel generator status and vehicle operating parameters of the electric mining truck in real time;

[0055] The intelligent control module uses a preset algorithm to calculate the optimal power distribution strategy based on the data from the power monitoring module;

[0056] The power switching module realizes seamless switching between electric and fuel power sources according to the instructions of the intelligent control module;

[0057] The energy consumption statistics module records and analyzes the energy consumption data of mining cards and provides feedback for optimization strategies.

[0058] It can be seen from the above that the present invention realizes real-time monitoring and precise control of the operating status of mining trucks by introducing intelligent control strategies, thereby effectively improving the efficiency of energy consumption management.

[0059] Furthermore, the intelligent control module uses a machine learning algorithm to continuously optimize the power distribution strategy based on historical energy consumption data. The machine learning algorithm is as follows:

[0060]

[0061] Among them, E 实 is the actual energy consumption, E 预 To predict energy consumption, n is the number of data samples;

[0062] At the same time, an energy consumption prediction algorithm is introduced to predict the future energy consumption of the vehicle. The formula of the energy consumption prediction algorithm is as follows:

[0063] E t+1 =f(E t ,E t-1 ,...,E t-n )

[0064] Among them, E t represents the energy consumption data at time t, f represents the prediction model, and n represents the time window size.

[0065] From the above, we can see that by training the machine learning model, we can find the optimal power distribution strategy to reduce energy consumption. At the same time, through the energy consumption prediction algorithm, we can predict future energy consumption and adjust the power distribution strategy according to the prediction results to further reduce energy consumption.

[0066] Furthermore, the power switching module has fault self-detection and emergency switching functions to ensure that the mining truck can still operate normally when any power source fails.

[0067] The performance indicators of the existing method and the extended-range electric mining truck energy consumption optimization management system provided by this embodiment are compared, and the comparison results are shown in Table 1:

[0068]

[0069]

[0070] It can be seen from the above table that the extended-range electric mining truck energy consumption optimization management system of this embodiment is superior to the current conventional technology in terms of energy consumption management, power source coordination efficiency, energy utilization rate, operational efficiency, degree of intelligence, adaptability and economy, and has significant advantages and benefits.

[0071] In summary, the system has the following beneficial effects:

[0072] 1) The present invention can monitor the energy consumption of the extended-range electric mining truck in real time, and optimize the working mode of the range extender and the output power of the drive motor according to the driving state of the vehicle and the power state of the battery, so as to improve the energy utilization rate;

[0073] 2) The present invention can effectively increase the range of the extended-range electric mining truck, reduce the number of charging times, and improve operational efficiency by optimizing the management of the working mode of the range extender and the output power of the drive motor;

[0074] 3) The present invention can effectively reduce the operating cost of extended-range electric mining trucks and improve the economic benefits of mines; by real-time monitoring and optimizing the management of energy consumption, it can reduce energy waste and fuel consumption, while extending the service life of batteries and reducing maintenance costs;

[0075] 4) The present invention can effectively improve the reliability and safety of the extended-range electric mining truck by real-time monitoring and control of the working status of the range extender and the drive motor; at the same time, by real-time monitoring and management of the battery's charge state and health state, the battery's service life and safety can be guaranteed.

[0076] like Figure 5 As shown, a method for optimizing energy consumption management of an extended-range electric mining truck comprises the following steps:

[0077] S1, the vehicle controller obtains the driving status of the vehicle and the power status of the battery;

[0078] S2, the vehicle controller controls the working mode of the range extender and the output power of the drive motor according to the vehicle's driving status and the battery power status;

[0079] S3, the range extender controller controls the working state of the engine and the generator to ensure that the output power of the range extender meets the needs of the vehicle;

[0080] S4. The drive motor drives the vehicle, and the gearbox adjusts the speed and torque of the drive motor.

[0081] From the above, it can be seen that the method can monitor the energy consumption of the extended-range electric mining truck in real time, optimize the management according to the driving status of the vehicle and the power status of the battery, and improve the energy utilization rate. At the same time, by optimizing the management of the working mode of the range extender and the output power of the drive motor, the method can effectively improve the cruising range of the extended-range electric mining truck, reduce the number of charging times, and improve operational efficiency. By real-time monitoring and control of the working status of the range extender and the drive motor, the method can improve the reliability and safety of the extended-range electric mining truck and ensure the normal operation of the vehicle. The method can reduce the operating cost of the extended-range electric mining truck by reducing energy waste and fuel consumption, while extending the service life of the battery and reducing maintenance costs.

[0082] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the above-mentioned extended-range electric mining truck energy consumption optimization management system is realized by adjusting the kernel parameters.

[0083] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0084] An embodiment of the present application provides a processor configured to execute the above-mentioned extended-range electric mining truck energy consumption optimization management system.

[0085] An embodiment of the present application provides a machine-readable storage medium, on which instructions are stored. When the instructions are executed by a processor, the processor is configured to execute the above-mentioned extended-range electric mining truck energy consumption optimization management system.

[0086] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0087] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0088] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0089] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0090] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0091] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0092] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0093] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0094] The embodiments of the present invention are provided for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. An energy consumption optimization management system for extended-range electric mining trucks, characterized by: Including vehicle controller, power battery management system, range extender controller, engine, generator, drive motor and gearbox; Among them, the vehicle controller is respectively connected to the power battery management system, the range extender controller, the drive motor and the gearbox, and the range extender controller is respectively connected to the engine and the generator.

2. The energy consumption optimization management system for extended-range electric mining trucks according to claim 1, characterized in that: The vehicle controller is used to control the working mode of the range extender and the output power of the drive motor according to the driving state of the vehicle and the power state of the battery; The power battery management system is used to monitor the battery power status and health status, and send the battery information to the vehicle controller; The range extender controller is used to control the working state of the engine and the generator; The engine is used to drive the generator to generate electricity; The generator is used to charge the drive motor and the battery; The driving motor is used to drive the vehicle; The gearbox is used to adjust the rotation speed and torque of the drive motor.

3. The energy consumption optimization management system for extended-range electric mining trucks according to claim 1, characterized in that: The power battery management system specifically includes: Power monitoring module, used to monitor the battery power, fuel generator status and vehicle operating parameters of the electric mining truck in real time; The intelligent control module uses a preset algorithm to calculate the optimal power distribution strategy based on the data from the power monitoring module; The power switching module realizes seamless switching between electric and fuel power sources according to the instructions of the intelligent control module; The energy consumption statistics module records and analyzes the energy consumption data of mining cards and provides feedback for optimization strategies.

4. The energy consumption optimization management system for extended-range electric mining trucks as claimed in claim 3, characterized in that: The intelligent control module uses a machine learning algorithm to continuously optimize the power distribution strategy based on historical energy consumption data.

5. The energy consumption optimization management system for extended-range electric mining trucks as claimed in claim 3, characterized in that: The power switching module has fault self-detection and emergency switching functions to ensure that the mining truck can still operate normally when any power source fails.

6. A method for optimizing energy consumption management of an extended-range electric mining truck as described in any one of claims 1 to 5, characterized in that: The following steps are involved: S1, the vehicle controller obtains the driving status of the vehicle and the power status of the battery; S2, the vehicle controller controls the working mode of the range extender and the output power of the drive motor according to the vehicle's driving status and the battery power status; S3, the range extender controller controls the working state of the engine and the generator to ensure that the output power of the range extender meets the needs of the vehicle; S4. The drive motor drives the vehicle, and the gearbox adjusts the speed and torque of the drive motor.

7. A processor, characterized in that: The system is configured to execute the energy consumption optimization management system for extended-range electric mining trucks according to any one of claims 1 to 5.

8. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is configured to execute the energy consumption optimization management system for extended-range electric mining trucks according to any one of claims 1 to 5.

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