A method for determining the power generation of a range-extended mine truck and related devices

Abstract

The application discloses a kind of power generation power determination method and related devices of range-extended mine truck, it is related to range-extended mine truck field, including based on the historical whole vehicle demand power in first time domain length before current time, predict target whole vehicle demand power in future second time domain length, based on target whole vehicle demand power and equivalent consumption minimization strategy, target equivalent factor is determined using dichotomy, make the actual SOC of power battery at the end of predicted time domain after current time convergence to power battery theoretical SOC, based on target equivalent factor and actual whole vehicle demand power, determine the target power generation power of range-extended mine truck using equivalent consumption minimization strategy.This application is according to predicted target whole vehicle demand power combined with equivalent consumption minimization strategy, determine the target equivalent factor of power battery actual SOC convergence to power battery theoretical SOC, according to target equivalent factor and actual whole vehicle demand power obtain the target power generation power that satisfies the actual running condition of range-extended mine truck.

Description

Technical Field

[0001] This invention relates to the field of range-extended mining truck technology, and more specifically, to a method and related apparatus for determining the power generation capacity of a range-extended mining truck. Background Technology

[0002] Range-extended mining trucks are mining transport trucks suitable for open-pit mines, powered by a range-extending system and a battery. Typical operating conditions for range-extended mining trucks include loading, fully loaded uphill driving, unloading, and unloaded downhill driving. Due to limitations in the power output of the range-extending system and the capacity of the battery, situations can arise where the truck lacks sufficient power (power generation + battery power) during fully loaded uphill driving, or the battery's state of charge (SOC) becomes too high during downhill driving, preventing regenerative braking.

[0003] Therefore, how to reasonably determine the power generation capacity based on the actual operating conditions of range-extended mining trucks has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention discloses a method and related apparatus for determining the power generation capacity of an extended-range mining truck, so as to reasonably determine the power generation capacity based on the actual operating conditions of the extended-range mining truck.

[0005] A method for determining the power generation capacity of a range-extended mining truck includes:

[0006] Based on the historical vehicle power demand within the first time domain before the current moment, predict the target vehicle power demand within the second time domain in the future.

[0007] Based on the target vehicle power demand and equivalent consumption minimization strategy, the target equivalent factor is determined by the bisection method, so that the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery.

[0008] Based on the target equivalence factor and the actual power demand of the vehicle, the target power generation of the range-extended mining truck is determined using the equivalent consumption minimization strategy.

[0009] Optionally, predicting the target vehicle power demand within a future second time domain based on historical vehicle power demand over a first time domain period prior to the current moment includes:

[0010] The historical vehicle demand power within the first time domain length before the current moment is input into a generalized regression neural network to predict the target vehicle demand power within the second time domain length in the future.

[0011] Optionally, the step of determining the target equivalence factor using a bisection method based on the target vehicle power demand and equivalent power consumption minimization strategy, so that the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery, includes:

[0012] Based on the value of the equivalent factor in the equivalent consumption minimization strategy, the theoretical power generation is determined when the power battery power does not exceed the power battery charging and discharging power limit.

[0013] The actual power of the power battery is obtained by the difference between the target vehicle power requirement and the theoretical power generation.

[0014] The actual SOC of the power battery is determined based on its actual power output.

[0015] Under the condition that the energy consumption cost of the extended-range mining truck corresponding to the actual SOC of the power battery is minimized, determine whether the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery.

[0016] If not, use the dichotomy method to adjust the value of the equivalent factor and return to the step of determining the theoretical power generation power when the power battery power does not exceed the power battery charging and discharging power limit;

[0017] If so, the equivalent factor corresponding to the convergence of the actual SOC of the power battery to the theoretical SOC of the power battery is determined as the target equivalent factor.

[0018] Optionally, the process for determining the theoretical SOC of the power battery includes:

[0019] Determine the initial SOC of the extended-range mining truck at the starting position and the final SOC at the ending position;

[0020] Determine the predicted time domain length and the total time for the extended-range mining truck to travel from the starting position to the ending position;

[0021] The theoretical SOC of the power battery is obtained based on the initial SOC, the final SOC, the predicted time domain length, and the total duration.

[0022] Optionally, the energy consumption cost of the range-extended mining truck is determined based on the actual SOC of the power battery, including:

[0023] Determine the change in SOC of the power battery at the current power generation rate;

[0024] Based on the SOC change, the actual SOC of the power battery, the theoretical SOC of the power battery, and the set energy consumption cost calculation strategy for the extended-range mining truck, the energy consumption cost of the extended-range mining truck corresponding to the actual SOC of the power battery is obtained.

[0025] Optionally, determining the target power generation of the range-extended mining truck based on the target equivalence factor and the actual power demand of the vehicle, using the equivalent consumption minimization strategy, includes:

[0026] When the equivalent factor in the equivalent consumption minimization strategy is the target equivalent factor, the power generation power is determined as the power generation power when the energy consumption cost of the extended-range mining truck corresponding to the actual vehicle power demand is minimized and the power battery power does not exceed the power battery charging and discharging power limit.

[0027] A device for determining the power generation capacity of a range-extended mining truck, comprising:

[0028] The power prediction unit is used to predict the target vehicle power demand in the second time domain based on the historical vehicle power demand in the first time domain before the current moment.

[0029] The equivalent factor determination unit is used to determine the target equivalent factor based on the target vehicle power demand and the equivalent consumption minimization strategy, using a bisection method, so that the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery.

[0030] The power generation determination unit is used to determine the target power generation of the range-extended mining truck based on the target equivalence factor and the actual power demand of the vehicle, using the equivalent consumption minimization strategy.

[0031] A storage medium storing at least one instruction, which, when executed by a processor, implements a method for determining the power generation capacity of any range-extended mining truck.

[0032] A controller, the controller comprising: a memory and a processor;

[0033] The memory is used to store at least one instruction;

[0034] The processor is used to execute the at least one instruction to implement a method for determining the power generation capacity of any extended-range mining truck.

[0035] A power generation determination system for a range-extended mining truck includes: a power battery, a slope sensor, a mass sensor, a storage medium, and a controller connected in series.

[0036] The power battery is used to provide electrical energy to the drive motor of the range-extended mining truck;

[0037] The slope sensor is used to collect the slope during the operation of the range-extended mining truck;

[0038] The mass sensor is used to collect the mass of the extended-range mining truck during operation.

[0039] As can be seen from the above technical solution, this invention discloses a method and related apparatus for determining the power generation capacity of a range-extended mining truck. Based on the historical vehicle power demand over a first time domain before the current moment, the target vehicle power demand over a second time domain is predicted. Based on the target vehicle power demand and an equivalent consumption minimization strategy, a bisection method is used to determine the target equivalence factor, ensuring that the actual SOC of the power battery at the end of the predicted time domain after the current moment converges to the theoretical SOC of the power battery. Based on the target equivalence factor and the actual vehicle power demand, an equivalent consumption minimization strategy is used to determine the target power generation capacity of the range-extended mining truck. This application first determines the target equivalence factor, based on the predicted target vehicle power demand and the equivalent consumption minimization strategy, so that the actual SOC of the power battery at the end of the predicted time domain after the current moment converges to the theoretical SOC of the power battery. This ensures that the power battery power corresponding to the actual SOC meets the actual demand. Then, based on the target equivalence factor and the actual vehicle power demand, the equivalent consumption minimization strategy is used again to obtain the target power generation capacity that meets the actual operating conditions of the range-extended mining truck. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the published drawings without creative effort.

[0041] Figure 1 This is a flowchart of a method for determining the power generation capacity of a range-extended mining truck disclosed in an embodiment of the present invention;

[0042] Figure 2 This is a schematic diagram illustrating the influence of an equivalent factor on the SOC trajectory, as disclosed in an embodiment of the present invention.

[0043] Figure 3 This is a flowchart of a method for determining the target equivalence factor using a bisection method based on a strategy for minimizing the target vehicle power demand and equivalent consumption, as disclosed in an embodiment of the present invention.

[0044] Figure 4 This is a schematic diagram of the uphill process of a range-extended mining truck disclosed in an embodiment of the present invention;

[0045] Figure 5 This is a schematic diagram of a device for determining the power generation capacity of a range-extended mining truck disclosed in an embodiment of the present invention;

[0046] Figure 6 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention;

[0047] Figure 7 This is a topology diagram of a power generation determination system for an extended-range mining truck disclosed in an embodiment of the present invention. Detailed Implementation

[0048] The technical solutions of 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.

[0049] This invention discloses a method and related apparatus for determining the power generation capacity of a range-extended mining truck. First, based on the predicted target vehicle power demand and an equivalent consumption minimization strategy, a target equivalent factor is determined to ensure that the actual SOC of the power battery at the predicted end time of the current time converges to the theoretical SOC of the power battery. This ensures that the power battery power corresponding to the actual SOC of the power battery meets the actual demand. Then, based on the target equivalent factor and combined with the actual vehicle power demand, the equivalent consumption minimization strategy is used again to obtain the target power generation capacity that meets the actual operating conditions of the range-extended mining truck.

[0050] See Figure 1 The present invention discloses a flowchart of a method for determining the power generation capacity of a range-extended mining truck, the method comprising:

[0051] Step S101: Based on the historical vehicle power demand within the first time domain before the current moment, predict the target vehicle power demand within the second time domain in the future.

[0052] The values ​​of the first time domain length and the second time domain length can be the same or different, depending on the actual needs, and this application does not impose any restrictions on them.

[0053] Specifically, the historical vehicle demand power within the first time domain length before the current moment is input into the Generalized Regression Neutral Network (GRNN) to predict the target vehicle demand power within the second time domain length in the future.

[0054] Generalized regressive neural networks are four-layer feedforward neural networks with good nonlinear approximation capabilities. They are an improved network based on radial basis function networks.

[0055] In practical applications, a sliding window method can be used to generate training samples for the generalized regression neural network: multiple time-domain segments of length T1+T2 are extracted from the historical vehicle demand power before the first time domain length. The historical vehicle demand power corresponding to the first T1 time domain length is the input, and the historical vehicle demand power corresponding to the second T2 time domain length is the output. After training the generalized regression neural network using the training samples, the historical vehicle demand power within the first time domain length before the current time can be input into the trained generalized regression neural network to predict the target vehicle demand power within the second time domain length in the future.

[0056] Step S102: Based on the target vehicle power demand and equivalent consumption minimization strategy, the target equivalent factor is determined by the bisection method, so that the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery.

[0057] SOC stands for State of charge.

[0058] The Equivalent Consumption Minimization Strategy (ECMS) is an energy management strategy for hybrid vehicles that aims to achieve the lowest possible fuel consumption or emissions by optimizing the power distribution between the electric motor and the internal combustion engine.

[0059] This application utilizes an equivalent consumption minimization strategy to optimize the power allocation between the power generation power and the power battery power in the total vehicle power demand, so as to minimize the energy consumption cost of the range-extended mining truck.

[0060] The equivalent factor in the equivalent consumption minimization strategy is a core parameter for achieving multi-objective optimization. In this application, the equivalent factor optimizes the relationship between power generation and battery power. The equivalent factor is positively correlated with SOC (State of Charge). See [link to relevant documentation]. Figure 2 The diagram shows the effect of the equivalent factor on the SOC trajectory. Figure 2 Curve 01 in the diagram indicates that a larger equivalent factor corresponds to a larger SOC, while curve 02 indicates that a smaller equivalent factor corresponds to a smaller SOC. Therefore, a reasonable equivalent factor can improve the accuracy of SOC. Curve 03 indicates that the SOC corresponding to a reasonable equivalent factor is the target SOC. Based on this, this application uses a bisection method to determine the target equivalent factor. This target equivalent factor is the equivalent factor by which the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery.

[0061] Step S103: Based on the target equivalence factor and the actual power demand of the vehicle, the target power generation of the range-extended mining truck is determined using the equivalent consumption minimization strategy.

[0062] The actual power requirement of the entire vehicle is determined based on the actual operating conditions of the range-extended mining truck.

[0063] In this application, the target equivalent factor is obtained by using an equivalent consumption minimization strategy based on the predicted target vehicle power demand. In order to meet the actual operating conditions of the extended-range mining truck, this application again uses an equivalent consumption minimization strategy for the target equivalent factor and the actual vehicle power demand, thereby obtaining a target power generation that conforms to the actual operating conditions of the extended-range mining truck.

[0064] In summary, this application discloses a method for determining the power generation capacity of a range-extended mining truck. Based on the historical vehicle power demand over a first time domain before the current moment, the target vehicle power demand over a second time domain is predicted. Based on the target vehicle power demand and an equivalent consumption minimization strategy, a bisection method is used to determine the target equivalence factor, ensuring that the actual SOC of the power battery at the end of the predicted time domain after the current moment converges to the theoretical SOC. Based on the target equivalence factor and the actual vehicle power demand, an equivalent consumption minimization strategy is used to determine the target power generation capacity of the range-extended mining truck. This application first determines the target equivalence factor, based on the predicted target vehicle power demand and the equivalent consumption minimization strategy, so that the actual SOC of the power battery at the end of the predicted time domain after the current moment converges to the theoretical SOC, ensuring that the power battery power corresponding to the actual SOC meets the actual demand. Then, based on the target equivalence factor and the actual vehicle power demand, the equivalent consumption minimization strategy is used again to obtain the target power generation capacity that meets the actual operating conditions of the range-extended mining truck.

[0065] In one embodiment, see Figure 3 This application discloses a flowchart of a method for determining the target equivalence factor using a bisection method based on a strategy to minimize the target vehicle power demand and equivalent consumption. The method includes:

[0066] Step S201: Based on the value of the equivalent factor in the equivalent consumption minimization strategy, determine the theoretical power generation when the power of the power battery does not exceed the power battery charging and discharging power limit.

[0067] In practical applications, when step S201 is executed for the first time, an initial value can be set for the equivalent factor in the equivalent consumption minimization strategy according to the actual situation. Since the equivalent factor mainly optimizes the relationship between power generation and power battery power, once the value of the equivalent factor is determined, the corresponding theoretical power generation can be obtained by limiting the power battery power to not exceed the power battery charging and discharging power limit.

[0068] Step S202: Obtain the actual power of the power battery based on the difference between the target vehicle power requirement and the theoretical power generation.

[0069] The required power of the vehicle consists of the power generated by the generator and the power of the battery. In this embodiment, the difference between the target required power of the vehicle and the theoretical power generated by the generator is taken as the actual power of the battery.

[0070] Step S203: Determine the corresponding actual SOC of the power battery based on the actual power of the power battery.

[0071] When determining the actual SOC of a power battery based on its actual power output, it is necessary to consider the characteristics of the power battery (e.g., the power output characteristics of the power battery), the real-time operating conditions of the power battery, and the SOC estimation method (e.g., the current integration method). For details, please refer to existing mature solutions, which will not be elaborated here.

[0072] Step S204: If the energy consumption cost of the extended-range mining truck corresponding to the actual SOC of the power battery is minimized, determine whether the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery. If not, proceed to step S205; if yes, proceed to step S206.

[0073] The process of determining the energy consumption cost of extended-range mining trucks based on the actual SOC of the power battery includes:

[0074] Determine the change in SOC of the power battery at the current power generation capacity. Based on the change in SOC, the actual SOC of the power battery, the theoretical SOC of the power battery, and the set energy consumption cost calculation strategy for the extended-range mining truck, obtain the energy consumption cost of the extended-range mining truck corresponding to the actual SOC of the power battery.

[0075] The energy consumption cost calculation strategy for range-extended mining trucks is shown in the following formula:

[0076] ;

[0077] In the formula, This indicates the energy consumption cost of range-extended mining trucks. Indicates the current time Power generation capacity, Indicates the current time The power generation capacity at the previous moment, express The corresponding engine fuel consumption, where 's' represents the equivalent factor. Indicates the current time The power generation capacity is The change in SOC of the power battery. Indicates power generation capacity. Actual SOC of the power battery at that time The theoretical state of charge (SOC) of the power battery is represented by p, which is the penalty coefficient for SOC deviation from the target; q is the cost coefficient for dynamic changes in the power generation of the range extender system; and z is the additional value of the SOC over-limit penalty. This is the upper limit of SOC. This is the lower limit of SOC.

[0078] Step S205: Adjust the value of the equivalent factor using the bisection method, and return to step S201.

[0079] The bisection method is a numerical computation and problem-solving algorithm. The basic idea is to divide the problem into two parts, then select one part to continue solving, and repeat this process until a solution is found or a specific condition is met.

[0080] This application is based on Figure 2 The principle behind the equivalent factor being too large leading to a larger SOC and the equivalent factor being too small leading to a smaller SOC is as follows: when it is determined that the value of the previous equivalent factor will cause the actual SOC of the power battery at the end of the predicted time domain after the current time to converge to the theoretical SOC of the power battery, the value of the equivalent factor will be adjusted using a bisection method, and the process will return to step S201 until the actual SOC of the power battery converges to the theoretical SOC of the power battery, thus obtaining the final target equivalent factor.

[0081] Step S206: Determine the equivalent factor corresponding to the convergence of the actual SOC of the power battery to the theoretical SOC of the power battery as the target equivalent factor.

[0082] The process for determining the theoretical SOC of a power battery includes:

[0083] (1) Determine the initial SOC of the range extender mining truck at the starting position and the final SOC at the ending position.

[0084] When the range extender mining truck is in an uphill state, the starting point of the range extender mining truck is the bottom of the slope, and the ending point is the top of the slope; when the range extender mining truck is in a downhill state, the starting point of the range extender mining truck is the top of the slope, and the ending point is the bottom of the slope.

[0085] For ease of subsequent discussion, the initial SOC of the range-extended mining truck at the starting position will be used as... This indicates that the SOC at the endpoint of the extended-range mining truck will be used... express.

[0086] In practical applications, This is a calibration value, and the specific value can be determined based on the SOC range of the power battery provided by the manufacturer. For example, when the endpoint is the top of a slope. It can be set to 70%, with the endpoint at the bottom of the slope. It can be set to 30%.

[0087] In practical applications, extended-range mining trucks are typically loaded and driven uphill at full load, then unloaded and driven downhill empty. Based on this, by using the mass sensors installed on the extended-range mining truck to collect the load status, it is possible to determine whether the truck is going uphill or downhill.

[0088] During the uphill process, the slope of the extended-range mining truck usually increases gradually, while during the downhill process, the slope usually decreases gradually. Therefore, by collecting the slope of the extended-range mining truck through the slope sensor installed on the truck, the uphill or downhill state can be determined based on the slope change.

[0089] See Figure 4 Taking an extended-range mining truck going uphill as an example, the distance the extended-range mining truck travels from starting point a to ending point b is S, and the gradient during the journey is θ, which is the angle between the tangent direction of the extended-range mining truck's journey and the horizontal plane. When the gradient is detected to gradually increase, it indicates that the extended-range mining truck is in an uphill state.

[0090] (2) Determine the predicted time domain length and the total time for the range-extended mining truck to travel from the starting position to the ending position.

[0091] Predicted time domain length The value of is determined according to actual needs, and this application does not impose any restrictions on it.

[0092] Total travel time of an extended-range mining truck from the starting point to the destination. This allows for timing of the extended-range mining truck's journey from the starting point to the ending point.

[0093] (3) The theoretical SOC of the power battery is obtained based on the initial SOC, the final SOC, the predicted time domain length and the total duration.

[0094] The theoretical SOC of a power battery is expressed as follows:

[0095] ;

[0096] In the formula, This represents the theoretical SOC of the power battery. This indicates the initial SOC of the range extender mining truck at the starting position. This indicates the SOC (State of Charge) at the destination location of the range-extended mining truck. This indicates the total time it takes for the extended-range mining truck to travel from the starting point to the ending point. Indicates the length of the prediction time domain. This indicates the duration of the current uphill or downhill phase.

[0097] In one embodiment, step S103 may specifically include:

[0098] When the equivalent factor in the equivalent consumption minimization strategy algorithm is the target equivalent factor, the power generation power is determined when the energy consumption cost of the extended-range mining truck corresponding to the actual vehicle power demand is minimized and the power battery power does not exceed the power battery charging and discharging power limit.

[0099] In practical applications, when the equivalent factor in the equivalent consumption minimization strategy algorithm is the target equivalent factor, the target power generation power corresponding to the minimum energy consumption cost of the extended-range mining truck and the power battery power not exceeding the power battery charging and discharging power limit is determined by using the energy consumption cost calculation formula of the extended-range mining truck.

[0100] Corresponding to the above method embodiments, this application also discloses a device for determining the power generation capacity of a range-extended mining truck.

[0101] See Figure 5 This application discloses a schematic diagram of a device for determining the power generation capacity of a range-extended mining truck. The device may include:

[0102] The power prediction unit 301 is used to predict the target vehicle power demand in the next second time domain based on the historical vehicle power demand in the first time domain before the current moment.

[0103] The values ​​of the first time domain length and the second time domain length can be the same or different, depending on the actual needs, and this application does not impose any restrictions on them.

[0104] The power prediction unit 301 can be used to: input the historical vehicle demand power within the first time domain length before the current moment into the generalized regression neural network, and predict the target vehicle demand power within the second time domain length in the future.

[0105] Generalized regressive neural networks are four-layer feedforward neural networks with good nonlinear approximation capabilities. They are an improved network based on radial basis function networks.

[0106] In practical applications, a sliding window method can be used to generate training samples for the generalized regression neural network: multiple time-domain segments of length T1+T2 are extracted from the historical vehicle demand power before the first time domain length. The historical vehicle demand power corresponding to the first T1 time domain length is the input, and the historical vehicle demand power corresponding to the second T2 time domain length is the output. After training the generalized regression neural network using the training samples, the historical vehicle demand power within the first time domain length before the current time can be input into the trained generalized regression neural network to predict the target vehicle demand power within the second time domain length in the future.

[0107] The equivalent factor determination unit 302 is used to determine the target equivalent factor based on the target vehicle power demand and the equivalent consumption minimization strategy, using a bisection method, so that the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery.

[0108] The Equivalent Consumption Minimization Strategy (ECMS) is an energy management strategy for hybrid vehicles that aims to achieve the lowest possible fuel consumption or emissions by optimizing the power distribution between the electric motor and the internal combustion engine.

[0109] This application utilizes an equivalent consumption minimization strategy to optimize the power allocation between the power generation power and the power battery power in the total vehicle power demand, so as to minimize the energy consumption cost of the range-extended mining truck.

[0110] The equivalent factor in the equivalent consumption minimization strategy is a core parameter for achieving multi-objective optimization. In this application, the equivalent factor optimizes the relationship between power generation and battery power. The equivalent factor is positively correlated with SOC (State of Charge). See [link to relevant documentation]. Figure 2 The diagram shows the effect of the equivalent factor on the SOC trajectory. Figure 2 Curve 01 in the diagram indicates that a larger equivalent factor corresponds to a larger SOC, while curve 02 indicates that a smaller equivalent factor corresponds to a smaller SOC. Therefore, a reasonable equivalent factor can improve the accuracy of SOC. Curve 03 indicates that the SOC corresponding to a reasonable equivalent factor is the target SOC. Based on this, this application uses a bisection method to determine the target equivalent factor. This target equivalent factor is the equivalent factor by which the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery.

[0111] The power generation determination unit 303 is used to determine the target power generation of the range-extended mining truck based on the target equivalence factor and the actual power demand of the vehicle, using the equivalent consumption minimization strategy.

[0112] The actual power requirement of the entire vehicle is determined based on the actual operating conditions of the range-extended mining truck.

[0113] In this application, the target equivalent factor is obtained by using an equivalent consumption minimization strategy based on the predicted target vehicle power demand. In order to meet the actual operating conditions of the extended-range mining truck, this application again uses an equivalent consumption minimization strategy for the target equivalent factor and the actual vehicle power demand, thereby obtaining a target power generation that conforms to the actual operating conditions of the extended-range mining truck.

[0114] In summary, this application discloses a device for determining the power generation capacity of a range-extended mining truck. Based on the historical vehicle power demand over a first time domain before the current moment, it predicts the target vehicle power demand over a second time domain. Based on the target vehicle power demand and an equivalent consumption minimization strategy, a bisection method is used to determine the target equivalence factor, ensuring that the actual SOC of the power battery at the end of the predicted time domain after the current moment converges to the theoretical SOC. Based on the target equivalence factor and the actual vehicle power demand, an equivalent consumption minimization strategy is used to determine the target power generation capacity of the range-extended mining truck. This application first determines the target equivalence factor, based on the predicted target vehicle power demand and the equivalent consumption minimization strategy, so that the actual SOC of the power battery at the end of the predicted time domain after the current moment converges to the theoretical SOC, ensuring that the power battery power corresponding to the actual SOC meets the actual demand. Then, based on the target equivalence factor and the actual vehicle power demand, the equivalent consumption minimization strategy is used again to obtain the target power generation capacity that meets the actual operating conditions of the range-extended mining truck.

[0115] In one embodiment, the equivalence factor determination unit 302 can be specifically used for:

[0116] Based on the value of the equivalent factor in the equivalent consumption minimization strategy, the theoretical power generation is determined when the power battery power does not exceed the power battery charging and discharging power limit.

[0117] The actual power of the power battery is obtained by the difference between the target vehicle power requirement and the theoretical power generation.

[0118] The actual SOC of the power battery is determined based on its actual power output.

[0119] Under the condition that the energy consumption cost of the extended-range mining truck corresponding to the actual SOC of the power battery is minimized, determine whether the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery.

[0120] If not, use the dichotomy method to adjust the value of the equivalent factor and return to the step of determining the theoretical power generation power when the power battery power does not exceed the power battery charging and discharging power limit;

[0121] If so, the equivalent factor corresponding to the convergence of the actual SOC of the power battery to the theoretical SOC of the power battery is determined as the target equivalent factor.

[0122] In one embodiment, the power generation determination device may further include:

[0123] Theoretical SOC determination unit, used for

[0124] Determine the initial SOC of the extended-range mining truck at the starting position and the final SOC at the ending position;

[0125] Determine the predicted time domain length and the total time for the extended-range mining truck to travel from the starting position to the ending position;

[0126] The theoretical SOC of the power battery is obtained based on the initial SOC, the final SOC, the predicted time domain length, and the total duration.

[0127] In one embodiment, the power generation determination unit may further include:

[0128] Energy cost determination unit, used for

[0129] Determine the change in SOC of the power battery at the current power generation rate;

[0130] Based on the SOC change, the actual SOC of the power battery, the theoretical SOC of the power battery, and the set energy consumption cost calculation strategy for the extended-range mining truck, the energy consumption cost of the extended-range mining truck corresponding to the actual SOC of the power battery is obtained.

[0131] In one embodiment, the power generation determination unit 303 can be specifically used for:

[0132] When the equivalent factor in the equivalent consumption minimization strategy is the target equivalent factor, the power generation power is determined as the power generation power when the energy consumption cost of the extended-range mining truck corresponding to the actual vehicle power demand is minimized and the power battery power does not exceed the power battery charging and discharging power limit.

[0133] Corresponding to the above embodiments, this application also discloses a storage medium that stores at least one instruction, which, when executed by a processor, implements the steps shown in the embodiments of the method for determining the power generation of an extended-range mining truck.

[0134] As a computer-readable storage medium, the storage medium can be used to store software programs, computer-executable programs and modules, data, etc., such as the program instructions / modules corresponding to the power generation determination, generalized regression neural network, and ECMS algorithm in the embodiments of the present invention. The controller executes the extended range mining truck power generation determination method of the above embodiments by running the software programs, instructions and modules stored in the storage medium and reading the change curve data therein.

[0135] The storage medium primarily includes a stored program area and a stored data area. The stored program area may store the operating system and at least one application program required for a given function; the stored data area may store data created based on terminal usage. Furthermore, the storage medium may include high-speed random access memory (RAM) and non-volatile memory, such as at least one disk drive, flash memory, or other non-volatile solid-state storage devices. In some instances, the storage medium may further include storage media remotely configured relative to the controller, which can be connected to the vehicle via a network, including but not limited to the Internet, corporate intranets, local area networks (LANs), mobile communication networks, and combinations thereof.

[0136] Corresponding to the above embodiments, such as Figure 6 As shown, the present invention also provides an electronic device, which may include: a processor 1 and a memory 2;

[0137] The processor 1 and memory 2 communicate with each other via communication bus 3.

[0138] Processor 1, for executing at least one instruction;

[0139] Memory 2 is used to store at least one instruction;

[0140] Processor 1 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.

[0141] Memory 2 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0142] In this embodiment, the processor executes at least one instruction to implement the steps shown in the method for determining the power generation capacity of an extended-range mining truck.

[0143] Corresponding to the above embodiments, see [link to relevant documentation]. Figure 7 The present application discloses a topology diagram of a power generation determination system for an extended-range mining truck. The system includes: a power battery 401, a slope sensor 402, a mass sensor 403, a storage medium 404, and a controller 405 connected to each other.

[0144] The power battery 401 is used to provide power to the drive motor of the range-extended mining truck.

[0145] The slope sensor 402 is used to collect the slope during the operation of the range-extended mining truck.

[0146] The mass sensor 403 is used to collect mass data during the operation of the extended-range mining truck.

[0147] For the working principles of storage medium 404 and controller 405, please refer to the corresponding sections of the above embodiments, which will not be repeated here.

[0148] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0149] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0150] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining the power generation capacity of a range-extended mining truck, characterized in that, include: Based on the historical vehicle power demand within the first time domain before the current moment, predict the target vehicle power demand within the second time domain in the future. Based on the target vehicle power demand and equivalent consumption minimization strategy, the target equivalent factor is determined by the bisection method, so that the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery. Based on the target equivalence factor and the actual power demand of the vehicle, the target power generation of the range-extended mining truck is determined by the equivalent consumption minimization strategy. The process for determining the theoretical SOC of the power battery includes: Determine the initial SOC of the extended-range mining truck at the starting position and the final SOC at the ending position; Determine the predicted time domain length and the total time for the extended-range mining truck to travel from the starting position to the ending position; The theoretical SOC of the power battery is obtained based on the initial SOC, the final SOC, the predicted time domain length, and the total duration.

2. The method for determining power generation capacity according to claim 1, characterized in that, The prediction of the target vehicle power demand in the second time domain based on the historical vehicle power demand within the first time domain period prior to the current moment includes: The historical vehicle demand power within the first time domain length before the current moment is input into a generalized regression neural network to predict the target vehicle demand power within the second time domain length in the future.

3. The method for determining power generation capacity according to claim 1 or 2, characterized in that, The strategy for minimizing the target vehicle power demand and equivalent power consumption, based on the target power demand and equivalent power consumption minimization strategy, uses a bisection method to determine the target equivalent factor, so that the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery, including: Based on the value of the equivalent factor in the equivalent consumption minimization strategy, the theoretical power generation is determined when the power battery power does not exceed the power battery charging and discharging power limit. The actual power of the power battery is obtained by the difference between the target vehicle power requirement and the theoretical power generation. The actual SOC of the power battery is determined based on its actual power output. Under the condition that the energy consumption cost of the extended-range mining truck corresponding to the actual SOC of the power battery is minimized, determine whether the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery. If not, use the dichotomy method to adjust the value of the equivalent factor and return to the step of determining the theoretical power generation power when the power battery power does not exceed the power battery charging and discharging power limit; If so, the equivalent factor corresponding to the convergence of the actual SOC of the power battery to the theoretical SOC of the power battery is determined as the target equivalent factor.

4. The method for determining power generation capacity according to claim 3, characterized in that, The energy consumption cost of the extended-range mining truck is determined based on the actual SOC of the power battery, including: Determine the change in SOC of the power battery at the current power generation rate; Based on the SOC change, the actual SOC of the power battery, the theoretical SOC of the power battery, and the set energy consumption cost calculation strategy for the extended-range mining truck, the energy consumption cost of the extended-range mining truck corresponding to the actual SOC of the power battery is obtained.

5. The method for determining power generation capacity according to claim 1, characterized in that, The process of determining the target power generation of the range-extended mining truck based on the target equivalence factor and the actual power demand of the vehicle, using the equivalent consumption minimization strategy, includes: When the equivalent factor in the equivalent consumption minimization strategy is the target equivalent factor, the power generation power is determined as the power generation power when the energy consumption cost of the extended-range mining truck corresponding to the actual vehicle power demand is minimized and the power battery power does not exceed the power battery charging and discharging power limit.

6. A device for determining the power generation capacity of a range-extended mining truck, characterized in that, include: The power prediction unit is used to predict the target vehicle power demand in the second time domain based on the historical vehicle power demand in the first time domain before the current moment. The equivalent factor determination unit is used to determine the target equivalent factor based on the target vehicle power demand and the equivalent consumption minimization strategy, using a bisection method, so that the actual SOC of the power battery at the predicted end time of the time domain after the current time converges to the theoretical SOC of the power battery. The power generation determination unit is used to determine the target power generation of the range-extended mining truck based on the target equivalence factor and the actual power demand of the vehicle, using the equivalent consumption minimization strategy. The power generation determination device further includes: Theoretical SOC determination unit, used for Determine the initial SOC of the extended-range mining truck at the starting position and the final SOC at the ending position; Determine the predicted time domain length and the total time for the extended-range mining truck to travel from the starting position to the ending position; The theoretical SOC of the power battery is obtained based on the initial SOC, the final SOC, the predicted time domain length, and the total duration.

7. A storage medium, characterized in that, The storage medium stores at least one instruction, which, when executed by a processor, implements the method for determining the power generation capacity of an extended-range mining truck as described in any one of claims 1 to 5.

8. A controller, characterized in that, The controller includes: a memory and a processor; The memory is used to store at least one instruction; The processor is used to execute the at least one instruction to implement the method for determining the power generation capacity of the extended-range mining truck as described in any one of claims 1 to 5.

9. A system for determining the power generation capacity of a range-extended mining truck, characterized in that, include: The connected power battery, slope sensor, mass sensor, storage medium as described in claim 7, and controller as described in claim 8; The power battery is used to provide electrical energy to the drive motor of the range-extended mining truck; The slope sensor is used to collect the slope during the operation of the range-extended mining truck; The mass sensor is used to collect the mass of the extended-range mining truck during operation.

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