A battery fire suppression parking space layout method and device for a new energy three-dimensional garage

Abstract

The present invention discloses a battery fire suppression parking space layout method and device for a new energy three-dimensional garage, including: (1) performing three-dimensional modeling on the three-dimensional garage; (2) based on the garage space model, determining the position set of potential lithium battery fire suppression parking spaces, where the potential lithium battery fire suppression parking spaces meet the preset limiting conditions; (3) establishing an evaluation index system and a comprehensive evaluation index; (4) screening the potential lithium battery fire suppression parking spaces according to the comprehensive evaluation index to obtain alternative berths; (5) constructing an objective function based on the emergency response coverage range, comprehensive evaluation index, and quantity distribution of each alternative berth; (6) using an improved genetic algorithm to optimize the objective function to obtain a lithium battery fire suppression parking space layout scheme and the corresponding number of lithium battery fire suppression parking spaces. The present invention can solve the technical problems in the prior art such as unreasonable layout of lithium battery fire suppression parking spaces, long fire extinguishing response time, and low resource utilization rate.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicle fire safety, and particularly to a method and device for layout of battery fire suppression parking spaces in a new energy multi-storey garage. Background Art

[0002] With the popularization of new energy vehicles, especially electric vehicles, the number of new energy vehicles parked in multi-storey garages is increasing continuously. New energy vehicles use lithium batteries as the main power source, and in case of fire, they have the characteristics of fast spread, high re-ignition rate, and great difficulty in extinguishing. Traditional fire extinguishing methods such as sprinkler fire extinguishing and dry powder fire extinguishing have limited effects on suppressing lithium battery fires and are difficult to meet the safety fire extinguishing requirements.

[0003] Immersion fire extinguishing technology is currently recognized as one of the most effective fire extinguishing methods for lithium battery fires. By completely immersing the burning electric vehicle in a water tank, the battery temperature can be rapidly reduced, and the spread and re-ignition of the fire can be effectively suppressed. In a stack-type multi-storey garage, special lithium battery fire suppression parking spaces (i.e., parking spaces with built-in water tanks) can be set on the first floor. When a vehicle is detected on fire, the stacker quickly transports the burning vehicle to the lithium battery fire suppression parking space for immersion fire extinguishing.

[0004] For example, Chinese patent document with publication number CN115177891A discloses a new energy vehicle parking space fire protection system, including a liftable parking board. A fire pool is arranged below the parking board, and a lifting mechanism is arranged in the fire pool. The lifting mechanism can drive the parking board to enter the fire pool downward; a water inlet pipe is arranged on the side wall of the lower part of the fire pool, and the water inlet pipe is connected to a water source through a drain valve.

[0005] Chinese patent document with publication number CN118454168A discloses a two-stage water storage fire protection device for new energy vehicles. The two-stage water storage fire protection device for new energy vehicles includes an upper water storage structure and a lower water storage structure connected up and down. The upper water storage structure adopts an inflation method and is internally provided with a gas generating device, which can generate gas after being activated to expand the upper water storage structure into a closed annular device, facilitating sleeving around the burning new energy vehicle; the lower water storage structure adopts a water filling method and is provided with a lower water storage type water injection port, which can achieve a weight pressing and sealing effect.

[0006] However, in the prior art, the layout of lithium battery fire suppression parking spaces mostly adopts empirical layout or uniform distribution method, lacking a systematic layout optimization method. This simple layout method often leads to the following problems: First, it cannot ensure that the burning vehicle is transported to the lithium battery fire suppression parking space within the specified emergency time; second, the number configuration of lithium battery fire suppression parking spaces is unreasonable, either too many resulting in resource waste or too few leading to safety risks; third, the location of lithium battery fire suppression parking spaces is unreasonable, affecting the normal operation efficiency of the garage.

[0007] Therefore, how to scientifically and reasonably layout the lithium battery fire suppression parking spaces, which can not only meet the requirements of the emergency fire extinguishing time for lithium battery fires, but also maximize the resource utilization efficiency, has become a key problem that urgently needs to be solved in the design and operation of new energy multi-storey garages. Summary of the Invention

[0008] The present invention provides a method and device for layout of battery fire suppression parking spaces in a new energy multi-storey garage, which can solve the technical problems such as unreasonable layout of lithium battery fire suppression parking spaces, long fire extinguishing response time, and low resource utilization rate in the prior art.

[0009] A method for layout of battery fire suppression parking spaces in a new energy multi-storey garage includes the following steps:

[0010] (1) Perform three-dimensional modeling on the multi-storey garage to obtain a garage space model, including parking space layout, traffic path network and operation parameters;

[0011] (2) Based on the garage space model, determine a set of positions of potential lithium battery fire suppression parking spaces, and the potential lithium battery fire suppression parking spaces meet preset limiting conditions;

[0012] (3) Establish an evaluation index system for potential lithium battery fire suppression parking spaces, and calculate the comprehensive evaluation index of each potential lithium battery fire suppression parking space;

[0013] (4) Screen the potential lithium battery fire suppression parking spaces according to the comprehensive evaluation index to obtain alternative berths;

[0014] (5) Based on the emergency response coverage, comprehensive evaluation index and quantity distribution of each alternative berth, construct an objective function;

[0015] (6) Use an improved genetic algorithm to optimize the objective function to obtain a layout plan for lithium battery fire suppression parking spaces and the corresponding number of lithium battery fire suppression parking spaces.

[0016] Further, in step (2), the preset limiting conditions include: being located on the first floor of the multi-storey garage, having a space for accommodating an immersion tank facility, meeting the requirements of the fire passage, having water supply and drainage conditions, and being located in a structurally load-bearing safe area.

[0017] Further, in step (3), the process of establishing the evaluation index system for potential lithium battery fire suppression parking spaces is as follows:

[0018] Based on the construction cost of each potential lithium battery fire suppression parking space, determine the construction cost index:

[0019] ;

[0020] Wherein, the The actual construction cost of a potential lithium - battery fire suppression parking space and respectively represent the maximum and minimum construction costs of all potential parking spaces;

[0021] Based on the number of parking spaces that each potential lithium - battery fire suppression parking space can serve, determine the service efficiency index:

[0022] ;

[0023] Among them, represents the number of parking spaces that the th potential lithium - battery fire suppression parking space can cover, represents the total number of parking spaces in the garage;

[0024] Based on the impact of the location of potential lithium - battery fire suppression parking spaces on the traffic flow in the garage and the use of parking spaces, determine the operation impact index:

[0025] ;

[0026] Among them, represents the average delay time of the traffic flow caused by the th potential lithium - battery fire suppression parking space, is the maximum allowable delay time threshold.

[0027] Calculate the comprehensive evaluation index of each potential lithium - battery fire suppression parking space. The specific process is as follows:

[0028] Based on the preset weights, perform weighted summation on the normalized construction cost index, service efficiency index, and operation impact index to obtain the comprehensive evaluation index. The formula is:

[0029] ;

[0030] Among them, , , are the weight coefficients of the construction cost index, service efficiency index, and operation impact index respectively, and satisfy .

[0031] Furthermore, in step (5), the objective function is expressed as:

[0032] ;

[0033] Among them, represents the reward item based on the emergency response coverage of alternative berths, represents the penalty item based on the total number of lithium - battery fire suppression parking spaces, Represents a penalty term based on the number of uncovered parking spaces; , , The formulas of are as follows:

[0034] ;

[0035] ;

[0036] ;

[0037] Wherein, Are the weight coefficients of reward, quantity penalty, and uncovered penalty respectively, Represents the comprehensive evaluation index of the th potential lithium battery fire suppression parking space, Is the evaluation threshold, Is the number of suppression parking spaces, Represents the total number of parking spaces in the garage, Is the total number of covered parking spaces.

[0038] Furthermore, in step (6), the specific steps of the improved genetic algorithm are as follows:

[0039] Initialize the population: Randomly generate a group of initial individuals, and each individual represents a layout plan for lithium battery fire suppression parking spaces;

[0040] Calculate the fitness: Calculate the fitness value of each individual according to the objective function;

[0041] Selection: Use the roulette wheel selection operator to select according to the fitness value of the individual. Individuals with higher fitness have a greater probability of being selected;

[0042] Crossover: Perform single-point crossover operation on the selected individuals to generate new individuals;

[0043] Mutation: Perform random mutation operation on the newly generated individuals;

[0044] Elite retention: Directly copy the individual with the highest fitness in the previous generation population to the next generation;

[0045] Dynamic parameter adjustment: Dynamically adjust the crossover probability and mutation probability according to the evolution of the population;

[0046] Termination condition: When the maximum number of iterations is reached or the fitness value meets the requirements, terminate the algorithm.

[0047] Further, in step (6), after obtaining the layout plan for the lithium battery fire suppression parking spaces, the following steps are also included: generating guiding drawings for the construction and implementation of the lithium battery fire suppression parking spaces; performing simulation verification on the emergency response time for the layout plan of the lithium battery fire suppression parking spaces to ensure that the fire extinguishing time requirement is met.

[0048] A device for layout of battery fire suppression parking spaces in a new energy multi-storey garage includes a memory and one or more processors. Executable code is stored in the memory, and when the one or more processors execute the executable code, it is used to implement the above-mentioned method for layout of battery fire suppression parking spaces.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. The present invention proposes a comprehensive multi-dimensional evaluation system, making the layout of the immersion berths more scientific and reasonable.

[0051] 2. By constructing an objective function including reward terms and penalty terms, the optimization process of the present invention can consider both safety and economy simultaneously, balancing the fire extinguishing efficiency and resource utilization.

[0052] 3. The present invention uses an improved genetic algorithm for optimization and solution, which can effectively avoid falling into local optimal solutions and improve the solution efficiency and the quality of the solution.

[0053] 4. The method of the present invention can ensure the optimal layout of the immersion berths under the constraint of the emergency time for lithium battery fires, improve the fire fighting and rescue efficiency of the new energy multi-storey garage, and reduce the safety risks and construction costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 FIG. is a flowchart of a method for layout of battery fire suppression parking spaces in a new energy multi-storey garage according to an embodiment of the present invention.

[0055] Figure 2 FIG. is a simplified diagram of a garage space model provided by an embodiment of the present invention.

[0056] Figure 3 FIG. is a flowchart of optimizing the objective function by using an improved genetic algorithm according to an embodiment of the present invention.

[0057] Figure 4 FIG. is the layout plan for the lithium battery fire suppression parking spaces finally obtained according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] The present invention will be further described in detail below with reference to the drawings and embodiments. It should be noted that the following embodiments are intended to facilitate the understanding of the present invention, but do not limit it in any way.

[0059] As Figure 1As shown in the figure, a method for arranging battery fire suppression parking spaces in a new energy three-dimensional garage includes the following steps:

[0060] Step 1: Perform three-dimensional modeling on the target area to obtain a garage space model.

[0061] Specifically, use three-dimensional modeling software to perform three-dimensional modeling on the new energy three-dimensional garage to completely reproduce the physical structure of the garage, including parking space layout, driving channels, elevator positions, entrance and exit positions, etc.

[0062] For example, in this embodiment, as Figure 2 shown, assume that the three-dimensional garage has a total of 5 floors and 225 parking spaces in total. The specific coordinates, dimensions, and distance relationships with other parking spaces of each parking space need to be recorded in detail. At the same time, the operating parameters of the garage need to be obtained, such as the operating speed, storage time, and vehicle entry and exit frequency of the palletizer / elevator.

[0063] In this embodiment, assume that the horizontal movement speed of the palletizer is 2.5 m / s, the vertical movement speed is 1.2 m / s, the storage time is 4 s, and the maximum emergency response time is 50 s. These parameters will be used for subsequent simulation analysis and optimization calculations to ensure that the selected suppression parking spaces can effectively handle any on-fire vehicle within the specified time.

[0064] Step 2: Determine the set of potential lithium battery fire suppression parking space positions.

[0065] Specifically, according to the preset limiting conditions, determine the potential positions of lithium battery fire suppression parking spaces. The limiting conditions include:

[0066] (1) Location limitation: Considering the particularity of the immersion fire extinguishing method, the suppression parking spaces must be set on the first floor of the three-dimensional garage to build a pool with sufficient depth.

[0067] (2) Space limitation: The suppression parking spaces need to have enough space to accommodate the immersion pool facilities, including the pool, drainage system, lifting equipment, etc. In this embodiment, assume that each suppression parking space requires at least 18 square meters of space to accommodate the immersion pool.

[0068] (3) Channel limitation: The suppression parking spaces cannot obstruct the normal traffic flow in the garage and need to meet the width and turning radius requirements of the fire channel. For example, the width of the fire channel is at least 4 meters, and the turning radius is at least 9 meters.

[0069] (4) Water supply and drainage limitation: The suppression parking spaces need to have a reliable water supply and drainage system that can quickly fill and drain water. Assume that it is required to fill the immersion pool within 5 minutes, and the drainage time does not exceed 8 minutes.

[0070] (5) Structural limitations: The load-bearing capacity of the floor structure where the parking spaces are located should be able to meet the weight requirements when the immersion pools are full. Assuming that the weight of each fully filled immersion pool is 25 tons, the load-bearing capacity must be greater than this value.

[0071] In this embodiment, assuming that according to the above limiting conditions, 20 potential suppression parking spaces are preliminarily determined, which are located at the 1st, 2nd, 3rd, 4th, 5th, 6th, 10th, 12th, 17th, 21st, 22nd, 26th, 30th, 33rd, 37th, 41st, 42nd, 43rd, 44th, and 45th parking spaces on the first floor respectively.

[0072] Step 3: Construct an evaluation index system and calculate the comprehensive evaluation index.

[0073] Specifically, for each potential suppression parking space, establish a multi-dimensional evaluation index system, including:

[0074] (1) Construction cost ( ): Consider land cost, equipment cost, installation cost, etc., and estimate the construction cost of suppression parking spaces at different locations. In this embodiment, assume that the construction costs of each parking space are as shown in Table 1 below.

[0075] Table 1

[0076]

[0077] In order to perform subsequent normalization processing, use the following formula to calculate the construction cost index:

[0078] ;

[0079] Where, is the actual construction cost of the th potential suppression parking space, is the highest construction cost (390,000 yuan) among all potential suppression parking spaces, is the lowest construction cost (170,000 yuan). After substituting the values, the construction cost indexes of each parking space are obtained, as shown in Table 2 below.

[0080] Table 2

[0081]

[0082] (2) Service efficiency ( ): Measure the number of parking spaces that the suppression parking space can serve, that is, within the specified emergency response time, the number of parking spaces that the palletizer can transport the on-fire vehicle to this suppression parking space.

[0083] In this embodiment, it is necessary to calculate the shortest transportation time from each potential suppression parking space to all parking spaces according to the specific size of the car body and the allowable speed of the palletizer. Finally, the number of parking spaces that each potential suppression parking space can cover within the maximum emergency response time of 50 s is counted, as shown in Table 3 below.

[0084] Table 3

[0085]

[0086] Calculate the service efficiency index of each potential suppression parking space according to the number of coverable parking spaces :

[0087] ;

[0088] The service efficiency indexes of each potential suppression parking space are obtained as shown in Table 4 below.

[0089] Table 4

[0090]

[0091] (3)Operation impact ( ):Evaluate the impact of the setting of suppression parking spaces on the normal traffic flow and parking space use in the garage, and minimize the impact on the garage operation efficiency.

[0092] In this embodiment, the average delay time caused by the suppression parking space to the traffic flow is used to measure the operation impact. Assume that the operation delay times of each parking space are as shown in Table 5 below.

[0093] Table 5

[0094]

[0095] Use the following formula to calculate the operation impact index:

[0096] ;

[0097] Among them, is the average delay time of the th potential suppression parking space to the traffic flow, and is the allowable maximum delay time (50 s in this example). After substituting the values, Table 6 is obtained.

[0098] Table 6

[0099]

[0100] After normalizing the above three indexes, set the weight coefficients 、 、 Calculate the comprehensive evaluation index of each potential suppression parking space through weighted summation .

[0101] In this embodiment, assume the weight coefficients (construction cost), (service efficiency), (operation impact), then the calculation results of the comprehensive evaluation index are shown in Table 7 below.

[0102] Table 7

[0103]

[0104] Step Four: Screen alternative berths.

[0105] Specifically, based on the comprehensive evaluation index ( ), preliminarily screen the potential suppression parking spaces, eliminate the obviously inappropriate ones, and obtain the set of alternative berths. For example, an evaluation threshold can be set. Only the potential suppression parking spaces where is greater than will be selected as alternative berths.

[0106] In this embodiment, assume the evaluation threshold is set, then the 10 parking spaces numbered 5, 6, 10, 17, 21, 26, 37, 41, 42, and 44 are selected as alternative berths.

[0107] Step Five: Construct the objective function.

[0108] Specifically, based on the set of alternative berths, construct an optimization objective function, which consists of three parts.

[0109] (1) Emergency response coverage reward term ( ): Encourage the layout of suppression parking spaces to cover more parking spaces and reduce the risk of failure to respond in a timely manner during a fire. The calculation formula is:

[0110] ;

[0111] Among them, is the reward term weight, is the number of selected suppression parking spaces, is the evaluation threshold.

[0112] (2) Suppression parking space quantity penalty term ( ): Considering the construction cost and service efficiency, try to reduce the number of suppression parking spaces. The calculation formula is:

[0113] ;

[0114] Among them, is the weight of the reward item, is the selected number of inhibited parking spaces.

[0115] (3) Penalty item for the number of uncovered parking spaces ( ): Penalty is imposed on the parking spaces that cannot be covered by the inhibited parking spaces to further reduce the fire risk. The calculation formula is:

[0116] ;

[0117] Among them, is the weight of the uncovered penalty item, is the total number of parking spaces in the garage, is the total number of parking spaces covered by the selected inhibited parking spaces.

[0118] The final objective function is:

[0119] ;

[0120] The objective of the present invention is to maximize the objective function Z.

[0121] Step Six: Use the improved genetic algorithm for optimization and solution.

[0122] Specifically, the improved genetic algorithm is used to optimize and solve the objective function, as Figure 3 shown. The algorithm steps are as follows:

[0123] (1) Encoding: Binary encoding is adopted. Each individual (chromosome) is represented by a binary string, where each bit represents whether a potential inhibited parking space is selected. For example, in this embodiment, there are 3 potential inhibited parking spaces (No. 1, No. 4, and No. 8), then an individual "101" represents selecting No. 1 and No. 8 parking spaces as inhibited parking spaces.

[0124] (2) Generation of the initial population: A random initial population containing M individuals is generated. In this embodiment, since there are only 3 potential inhibited parking spaces, to ensure the algorithm efficiency, the initial population size M can be set to a relatively small value, such as M = 5.

[0125] (3) Fitness function: The fitness function value of an individual directly adopts the value of the objective function Z. That is:

[0126] ;

[0127] Among them, represents the fitness value of the th individual, represents the objective function value corresponding to the th individual.

[0128] (4) The Roulette Wheel Selection method is adopted. The probability of each individual being selected is proportional to its fitness value. The individual The specific calculation formula for the probability of being selected is as follows:

[0129] ;

[0130] (5) Crossover operation: Single-Point Crossover is adopted. Randomly select two parent individuals and randomly select a crossover point, and exchange the gene segments after the crossover point of the two parent individuals to generate two new offspring individuals. The crossover operation is performed with a certain probability and in this embodiment it is set to 0.9.

[0131] (6) Mutation operation: Bitwise Mutation is adopted. For each gene of each individual, it is mutated with a certain probability (changing 0 to 1 and 1 to 0). In this embodiment it is set to 0.05.

[0132] To increase the diversity of the population and avoid premature convergence of the algorithm, a mutation operation based on neighborhood search is proposed here:

[0133] Trigger neighborhood search mutation with a certain probability (such as 0.1). For the selected mutated individual, randomly select an unselected potential inhibitory parking space (if any) and add it to the layout scheme of the individual. Calculate the fitness value of the individual after adding the new parking space. If the fitness value improves, accept this mutation; otherwise, accept the worse solution with a certain probability (such as 0.5).

[0134] (7) Elite retention strategy: To avoid the loss of the optimal solution during the evolution process, the elite retention strategy is adopted. The individual with the highest fitness in each generation is directly copied to the next generation.

[0135] (8) Dynamic parameter adjustment, including:

[0136] Dynamic crossover probability: The crossover probability gradually decreases as the number of iterations increases. The initial value is set to 0.9, and after every certain number of generations (such as 10 generations), = * decay coefficient (such as 0.95).

[0137] Dynamic mutation probability: The mutation probability gradually increases as the number of iterations increases. The initial value is set to 0.05, and after every certain number of generations (such as 10 generations), = * Growth coefficient (e.g., 1.05), with an upper limit of 0.2.

[0138] The specific implementation process of the improved genetic algorithm is as follows: (continuing with the example of screening out 10 potential inhibited parking spaces above)

[0139] (1) Parameter setting: Population size M = 20; Maximum number of iterations ; ; Initial crossover probability , Decay coefficient 0.95; Initial mutation probability , Growth coefficient 1.05, with an upper limit of 0.2; Neighborhood search mutation trigger probability: 0.1; Probability of accepting a worse solution: 0.5; Weight coefficient: , , , .

[0140] (2) Initialize the population:

[0141] Randomly generate 20 individuals. For example:

[0142] Individual 1: "1000110101" means selecting parking spaces No. 5, 21, 26, 41, and 44 as inhibited parking spaces (the 1st digit represents No. 5, the 2nd digit represents No. 6, the 3rd digit represents No. 10, the 4th digit represents No. 17, the 5th digit represents No. 21, the 6th digit represents No. 26, the 7th digit represents No. 37, the 8th digit represents No. 41, the 9th digit represents No. 42, and the 10th digit represents No. 44. '1' means selected, '0' means not selected)

[0143] Individual 2: "0100000000" means selecting parking space No. 6 as an inhibited parking space.

[0144] Individual 3: "0000000001" means selecting No. 44 as an inhibited parking space.

[0145] ……

[0146] (3) Calculate the fitness:

[0147] According to the encoding of each individual, calculate its corresponding value and use it as the fitness value of this individual

[0148] (4) Iterative evolution (selection, crossover, mutation, elitist retention):

[0149] Selection: According to the roulette wheel selection method, select 10 individuals to enter the next generation.

[0150] Crossover: With a probability of Perform single-point crossover on the selected individuals.

[0151] Mutation: With a probability of perform basic bit mutation on the individuals and trigger neighborhood search mutation with a probability of 0.1.

[0152] Elite retention: Directly copy the individual with the highest fitness in the current population to the next generation.

[0153] (5) Dynamic adjustment: Update and .

[0154] (6) Termination condition judgment: If the maximum number of iterations reaches 100 generations, or the optimal solution has not improved for 10 consecutive generations, stop the iteration.

[0155] (7) Output result: If the optimal solution output is "1000110101", it corresponds to selecting parking spaces No. 5, No. 12, No. 21, No. 26, and No. 41 as the lithium battery fire suppression parking spaces.

[0156] Through the above improved genetic algorithm, the final layout plan of the lithium battery fire suppression parking spaces can be obtained, as Figure 4 shown.

[0157] Based on the same inventive principle, an embodiment of the present invention further provides a device for arranging lithium battery fire suppression parking spaces in a new energy multi-story garage, including a memory and one or more processors. When the one or more processors execute the executable code stored in the memory, they are used to implement the method for arranging lithium battery fire suppression parking spaces mentioned in the above embodiment.

[0158] Based on the same inventive principle, an embodiment of the present invention further provides a device for arranging lithium battery fire suppression parking spaces in a new energy multi-story garage, including:

[0159] An input module, configured to receive three-dimensional model data of the multi-story garage and construct a garage space model;

[0160] A storage module, configured to store data such as the garage space model, the set of potential lithium battery fire suppression parking space positions, the comprehensive evaluation index of each potential parking space, the selected alternative berths, and the constructed optimization objective function;

[0161] A calculation module, configured to determine the set of potential lithium battery fire suppression parking space positions; calculate the comprehensive evaluation index of each potential parking space; screen the alternative berths according to the comprehensive evaluation index; construct an optimization objective function, and use an improved genetic algorithm to solve the objective function to obtain the optimal layout plan;

[0162] An output module for outputting the finally determined layout plan for lithium battery fire suppression parking spaces in a three-dimensional garage.

[0163] Through the establishment of a multi-dimensional evaluation system, the present invention comprehensively considers construction costs, service efficiency, and operational impacts, making the layout of lithium battery fire suppression parking spaces in a three-dimensional garage more scientific and reasonable. At the same time, the improved genetic algorithm adopted can effectively avoid falling into local optima through methods such as dynamically adjusting parameters, elitist retention strategies, and neighborhood search mutations, ensuring the global optimization ability and solution efficiency. The finally obtained layout plan minimizes construction and operation costs to the greatest extent on the premise of meeting fire safety requirements.

[0164] The method proposed by the present invention is not only applicable to newly built three-dimensional garages but also can be used for the fire protection transformation and upgrading of existing three-dimensional garages. By evaluating the existing conditions of the garage and performing optimization calculations, the best positions and quantities of lithium battery fire suppression parking spaces can be quickly and accurately determined, providing a strong guarantee for the safe operation of new energy three-dimensional garages. In addition, the method proposed by the present invention has a certain degree of generality and can also be used for the layout optimization of fire protection facilities in other types of facilities, such as large warehouses and logistics centers, after appropriate modification.

[0165] The above-described embodiments have elaborated in detail the technical solutions and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the present invention. Any modifications, supplements, and equivalent replacements made within the scope of the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A battery fire suppression parking space layout method for a new energy three-dimensional garage, characterized in that, It includes the following steps: (1) Conduct 3D modeling on the stereoscopic garage to obtain a garage space model, including parking space layout, traffic path network, and operation parameters; (2) Based on the garage space model, determine the set of positions of potential lithium battery fire suppression parking spaces, where the potential lithium battery fire suppression parking spaces meet the preset restrictive conditions; (3) Establish an evaluation index system for potential lithium battery fire suppression parking spaces, and calculate the comprehensive evaluation index for each potential lithium battery fire suppression parking space; (4) According to the comprehensive evaluation index, screen the potential lithium battery fire suppression parking spaces to obtain alternative berths; (5) Based on the emergency response coverage, comprehensive evaluation index, and quantity distribution of each alternative berth, construct an objective function; the objective function is expressed as: ； Among them, represents the reward item based on the emergency response coverage of alternative berths, represents the penalty item based on the total number of lithium battery fire suppression parking spaces, represents the penalty item based on the number of uncovered parking spaces; , , The formulas of ； ； ； Among them, are the weight coefficients of reward, quantity penalty, and uncovered penalty respectively, represents the comprehensive evaluation index of the th potential lithium battery fire suppression parking space, is the evaluation threshold, is the number of suppression parking spaces, represents the total number of parking spaces in the garage, is the total number of covered parking spaces; (6) Use the improved genetic algorithm to optimize the objective function to obtain the layout plan of lithium battery fire suppression parking spaces and the corresponding number of lithium battery fire suppression parking spaces.

2. The battery fire suppression parking space layout method for the new energy three-dimensional garage according to claim 1, characterized in that, In step (2), the preset restrictive conditions include: being located on the first floor of the stereoscopic garage, having a space to accommodate an immersion pool facility, meeting the fire passage requirements, having water supply and drainage conditions, and being located in a structurally load-bearing safe area.

3. The battery fire suppression parking space layout method for the new energy three-dimensional garage according to claim 1, characterized in that In step (3), the process of establishing the evaluation index system for potential lithium battery fire suppression parking spaces is as follows: Based on the construction cost of each potential lithium battery fire suppression parking space, determine the construction cost index: ； in, No. The actual construction cost of a potential lithium battery fire suppression parking space, and Respectively represent the maximum and minimum construction costs of all potential parking spaces; Based on the number of parking spaces that each potential lithium battery fire suppression parking space can serve, determine the service efficiency index: ； Among them, represents the number of parking spaces that can be covered by the th potential lithium battery fire suppression parking space, and represents the total number of parking spaces in the garage; Based on the impact of the position of the potential lithium battery fire suppression parking space on the traffic flow in the garage passage and the use of parking spaces, determine the operation impact index: ； in, Indicates The average delay time of traffic flow caused by potential lithium battery fire suppression parking spaces, The maximum allowed delay time threshold.

4. The battery fire suppression parking space layout method for the new energy three-dimensional garage according to claim 3, characterized in that, In step (3), the process of calculating the comprehensive evaluation index for each potential lithium battery fire suppression parking space is as follows: Based on the preset weights, perform weighted summation on the normalized construction cost index, service efficiency index, and operation impact index to obtain the comprehensive evaluation index. The formula is: ； Among them, , , are the weight coefficients of the construction cost index, service efficiency index, and operation impact index respectively, and satisfy .

5. The battery fire suppression parking space layout method of the new energy three-dimensional garage according to claim 1, characterized in that, In step (6), the specific steps of the improved genetic algorithm are as follows: Initialize the population: Randomly generate a group of initial individuals, and each individual represents a layout plan of lithium battery fire suppression parking spaces; Calculate the fitness: Calculate the fitness value of each individual according to the objective function; Selection: Use the roulette wheel selection operator to select according to the fitness value of the individual. Individuals with higher fitness values have a greater probability of being selected; Crossover: Perform single-point crossover operation on the selected individuals to generate new individuals; Mutation: Perform random mutation operation on the newly generated individuals; Elite retention: Directly copy the individual with the highest fitness value in the previous generation population to the next generation; Dynamic parameter adjustment: Dynamically adjust the crossover probability and mutation probability according to the evolution of the population; Termination condition: When the maximum number of iterations is reached or the fitness value meets the requirements, terminate the algorithm.

6. The battery fire suppression parking space layout method for the new energy three-dimensional garage according to claim 1, wherein In step (6), after obtaining the layout plan of lithium battery fire suppression parking spaces, it further includes: generating guiding drawings for the construction and implementation of lithium battery fire suppression parking spaces; for the layout plan of lithium battery fire suppression parking spaces, conduct emergency response time simulation verification to ensure that the fire extinguishing time requirements are met.

7. A battery fire suppression parking space layout device for a new energy three-dimensional garage, characterized in that, Comprising a memory and one or more processors, wherein executable code is stored in the memory, and when the one or more processors execute the executable code, it is used to implement the battery fire suppression parking space layout method according to any one of claims 1-6.

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