A fuel cell tram energy management method based on pseudo-spectral and PSO algorithm

Abstract

The present invention relates to a fuel cell tram energy management method based on pseudo-spectrum and PSO algorithm, comprising the following steps: step 1: establishing a fuel cell tram scene environment model; step 2: establishing a simple structural model and a dynamic model of the fuel cell tram; step 3: optimizing the speed trajectory of the fuel cell tram using pseudo-spectrum method; step 4: calculating the required power of the fuel cell tram based on the optimized speed; step 5: optimizing the output power of the fuel cell and the power battery using particle swarm algorithm PSO. The scheme of the present invention is oriented to the fuel cell tram in the city, considering the influence of the traffic lights between two stations on the running state of the fuel cell tram; optimizing the speed trajectory of the fuel cell tram between traffic lights, so that the fuel cell tram can pass the traffic light intersection without stopping, and using the particle swarm algorithm to efficiently and reasonably allocate the output power of the fuel cell and the power battery to achieve energy-saving driving.

Description

Technical Field

[0001] The present invention belongs to the technical field of urban intelligent transportation, and in particular relates to an energy management method for a fuel cell tram based on pseudo-spectrum and PSO algorithm. Background Art

[0002] In recent years, with the development of urbanization, the growth of urban population and vehicles, environmental and traffic problems have become increasingly serious, which has also brought severe challenges to the development of cities. The urban rail transit solution stands out from other solutions with its advantages such as large passenger capacity and green and low carbon. Urban rail transit includes subways, light rails and trams. Trams are favored by more and more small and medium-sized cities with their advantages such as light weight, flexible formation and lower investment cost than subways and light rails. Among them, fuel cell hybrid trams powered by hydrogen have become a hot spot for tram technology research and application at home and abroad with their energy saving, environmental protection and high efficiency.

[0003] Due to the characteristics of fuel cells, if fuel cells are used as a separate power source, they cannot achieve a rapid response to power. This requires an additional auxiliary power system to match the fuel cell, which can not only quickly respond to larger power demands, but also recover energy during braking of the tram, effectively improving the overall efficiency of the vehicle. At present, most of the research on energy management of hybrid systems at home and abroad is concentrated in the automotive field, while there are fewer studies on energy management of fuel cell trams. Existing energy management strategies can generally be divided into two categories, one is a rule-based energy management strategy, and the other is an energy management strategy based on optimization algorithms. Most of these two energy management strategies simply distribute the required power to the two energy sources, and do not combine the predicted speed for energy management, resulting in poor energy management results.

[0004] Energy management for hybrid trams is highly dependent on speed planning, and it is necessary to determine the required power and distribute the power according to the speed. To this end, this application takes fuel cell trams as the research object, and optimizes the speed trajectory between two tram stations by means of communication between fuel cell trams and transportation infrastructure, combined with traffic light information on the road, to reduce the rapid speed change or idling behavior of the tram, and based on the optimized speed trajectory, combined with energy management strategies, ultimately achieve energy-saving travel for fuel cell trams and minimize energy consumption during operation. Summary of the invention

[0005] The purpose of the present invention is to provide a fuel cell tram energy management method based on pseudo-spectrum and PSO algorithm to solve the problem that when a fuel cell tram shares roads and traffic lights with motor vehicles, the fuel cell tram forms a speed trajectory between two stations that allows the fuel cell tram to pass through traffic lights without stopping, and perform energy management according to the optimized speed trajectory to achieve the goal of minimizing the operating energy consumption of the fuel cell tram.

[0006] In order to solve the above technical problems, the technical solution of the present invention is to provide a fuel cell tram energy management method based on pseudo spectrum and PSO algorithm, and its innovation lies in: comprising the following steps:

[0007] Step 1: Establish a scene environment model of a fuel cell tram;

[0008] Step 2: Establish a simple structural model and a dynamic model of the fuel cell tram, and construct inequality constraints of the dynamic model based on the maximum and minimum values ​​of the power data of the fuel cell power, power battery power, and motor power of the fuel cell tram and the dynamic model;

[0009] Step 3: The fuel cell tram obtains the distance between the fuel cell tram and the traffic light intersection and the traffic light phase with the help of the vehicle infrastructure interconnection system V2I, and optimizes the speed trajectory of the fuel cell tram using the pseudo-spectral method;

[0010] Step 4: Based on the optimized speed and the simple structural model and dynamic model of the fuel cell tram, calculate the required power P of the fuel cell tram req (t) and the power balance relationship of the fuel cell tram.

[0011] Step 5: According to the required power of the fuel cell tram, the SOC of the power battery is used as the state variable, the fuel cell power is used as the control variable, and the minimum total energy consumption of the tram operation is used as the optimization objective function J e Under the constraints of the dynamic model in step 2, the particle swarm algorithm PSO is used to allocate the required power of the fuel cell tram, and the required power is efficiently and reasonably allocated to the fuel cell and the power battery to perform energy management of the fuel cell tram.

[0012] Furthermore, the scene environment model of the fuel cell tram established in the step 1 is specifically as follows: on a certain city road, two adjacent tram stations are set as A and B, station A is the starting station, station B is the ending station, and a crossroads with a traffic light is set between station A and station B, and the distance between the traffic light and station A is S1, and the distance between the traffic light and station B is S2; assuming that the fuel cell tram starts from station A at an initial speed v0, when it arrives at the crossroads, it is determined whether the tram stops according to the phase of the traffic light, wherein the tram must stop when the red light phase is red; during the driving process of the fuel cell tram, the fuel cell tram obtains the traffic light signal through the vehicle infrastructure interconnection system V2I.

[0013] Furthermore, the specific structure of the simplified structural model of the fuel cell tram in step 2 is as follows: the fuel cell is connected to the busbar through a unidirectional DC / DC converter; the power battery is connected to the busbar, and a DC / AC converter is added to the busbar to connect to the motor, and the fuel cell and the power battery are both connected to the motor to drive the motor together or individually;

[0014] The dynamic model of the fuel cell tram is expressed as:

[0015]

[0016]

[0017] Among them, F t (t) represents the traction force required during the operation of the fuel cell tram; P req (t) represents the required power of the fuel cell tram according to the required traction and vehicle speed; m represents the mass of the fuel cell tram, g represents the acceleration of gravity; α represents the road angle; w0 represents the unit basic resistance; G d represents the total mass of the fuel cell tram including the rotating mass; v represents the speed of the fuel cell tram; η DC / AC Indicates the efficiency of the DC / AC converter; η M Indicates the efficiency of the motor; η T Represents the transmission efficiency of the system; According to the simple structural model of the fuel cell tram, the power balance relationship of the fuel cell tram is:

[0018] P req (t) = P fc (t)·η DC / DC +P bat (t)

[0019] Where P fc , P bat , η DC / DCThey represent the fuel cell power, power battery power and efficiency of the DC / DC converter respectively.

[0020] Furthermore, the unit basic resistance w0 in the fuel cell tram dynamics model and the total mass G of the fuel cell tram including the rotating mass d Can be expressed as:

[0021]

[0022] Where a, b, c are resistance parameters, v represents vehicle speed, and γ represents the rotational mass coefficient.

[0023] Furthermore, the fuel cell, power battery and motor included in the simple structural model of the fuel cell tram, for the fuel cell, in order to simplify the calculation, the internal model of the fuel cell is not considered, only the power output of the fuel cell is considered, and the maximum and minimum power of the fuel cell are set as constraints; for the power battery, a simple and effective equivalent battery model is used to express the internal state of the battery, and the relationship between the battery internal resistance and the open circuit voltage is expressed as:

[0024]

[0025] Wherein, OCV represents the open circuit voltage; i bat Represents the circuit current, R int Indicates the internal resistance of the battery; C bat represents the battery capacity; SOC0 represents the initial state of charge of the battery; SOC(t) represents the state of charge of the battery at each moment; for the motor, the influence of the motor transient response is not considered, and the motor efficiency is simplified to a function related to the motor speed and torque, which can be expressed as:

[0026] η M (ω MG ,T MG ) = f MG (ω MG ,T MG )

[0027] Where η M Represents the efficiency of the motor, ω MG Indicates the motor speed, T MG Represents the torque of the motor, f MG It represents the functional relationship between the motor speed torque and motor efficiency.

[0028] Furthermore, the inequality constraint for constructing the dynamic model in step 2 is specifically expressed as:

[0029] P fc,min <P fc (t)<P fc,max

[0030] P bat,min <P bat (t)<P bat,max

[0031] P mot,min <P mot (t)<P mot,max

[0032] SOC min <SOC(t)<SOC max

[0033] Where P fc (t),P fc,min ,P fc,max Respectively represent the real-time power of the fuel cell and its minimum and maximum power; P bat (t),P bat,min ,P bat,max , respectively represent the real-time power of the power battery and its minimum and maximum power: P mot (t),P mot,min ,P mot,max , respectively represent the real-time power of the motor and its minimum and maximum power; SOC(t) represents the charge state of the battery at each moment, i.e. SOC, SOC min Indicates the minimum value of the power battery SOC, SOC max Indicates the maximum value of the power battery SOC.

[0034] Furthermore, the specific process of using the pseudo-spectral method to optimize the speed trajectory of the fuel cell tram in step 3 is: according to the scene environment model established in step 1, combined with the dynamic model of the fuel cell tram and the traffic light phase information obtained by the vehicle infrastructure interconnection system V2I and the status information between the two stations, combined with the maximum speed, maximum and minimum acceleration, maximum and minimum braking force, and maximum and minimum traction of the fuel cell tram, the pseudo-spectral method is used to obtain the optimal speed sequence from station A to station B under constraints, so that the fuel cell tram can pass through the traffic light intersection without stopping, thereby optimizing the speed trajectory of the fuel cell tram.

[0035] Furthermore, the optimization objective function J in step 5 is e The selection of the fuel cell hydrogen H2 consumption and the power battery equivalent H2 consumption is selected as the optimization objective function J e , specifically expressed as:

[0036]

[0037] In the formula, J eRepresents the optimization objective function, that is, the total minimum energy consumption, where represents the hydrogen consumption rate of the fuel cell, represents the equivalent hydrogen consumption rate of the power battery, and ξ represents the adjustment coefficient introduced into the optimization objective function.

[0038] Furthermore, the objective function J is optimized e In The specific expressions of and ξ are as follows:

[0039]

[0040]

[0041]

[0042] Where P fc (t) represents the real-time power of the fuel cell, P bat (t) represents the real-time power of the power battery, η fc represents the efficiency of the fuel cell, η DC / AC Indicates the efficiency of the DC / DC converter, and LHV stands for the lower heating value of hydrogen.

[0043] Compared with the existing invention, the beneficial effects of the present invention are:

[0044] (1) In the case where fuel cell trams and motor vehicles share roads and traffic lights in cities, the impact of traffic lights between two stations on the operating status of fuel cell trams is considered;

[0045] (2) Based on the traffic light timing information obtained by V2I, the running speed trajectory of the fuel cell tram between two stations with traffic lights in between is optimized, so that the fuel cell tram can pass the traffic light intersection without stopping;

[0046] (3) Based on the optimized speed sequence, the fuel cell tram is energy managed to minimize the running energy consumption of the tram;

[0047] (4) The present invention takes fuel cell trams as the research object, considers the constraints of fuel cell trams such as braking energy, speed limit, acceleration, maximum output power of fuel cells and power batteries, and uses pseudo-spectral method to solve the optimal speed sequence under the fuel cell tram environment model, and then uses PSO algorithm to implement energy management strategy for fuel cell trams based on this optimal speed sequence. First, by optimizing the speed and then performing energy management based on the optimized speed, compared with the energy management method of simply performing energy distribution, the output power of fuel cells and power batteries can be efficiently and reasonably distributed to achieve the most energy-efficient driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0049] Figure 1 It is a flow chart of the present invention.

[0050] Figure 2 It is a schematic diagram of a fuel cell tram of the present invention.

[0051] Figure 3 It is the optimized speed position diagram of the fuel cell tram.

[0052] Figure 4a This is a graph of the change of power battery SOC over time under two strategies.

[0053] Figure 4b This is a graph showing the change in fuel cell hydrogen consumption over time under the two strategies.

[0054] Figure 5a It is a graph showing the power of the fuel cell changing with time under the two strategies.

[0055] Figure 5b This is a graph showing the power of the power battery changing over time under the two strategies. DETAILED DESCRIPTION

[0056] In order to illustrate the technical solution of the present invention, further description is given below in conjunction with the accompanying drawings and specific implementation methods.

[0057] The present invention provides a fuel cell tram energy management method based on pseudo spectrum and PSO algorithm, which is specifically as follows Figure 1 As shown, the following steps are included:

[0058] Step 1: Establish a scene environment model of a fuel cell tram: The scene-based environment model of a fuel cell tram is specifically as follows: on a certain city road, two adjacent tram stations are set as A and B, station A is the starting station, station B is the terminal station, and there is a crossroads with a traffic light between station A and station B. In this embodiment, the distance between the traffic light and the starting platform A is 1 km, and the distance between the traffic light and the terminal platform B is 1 km; assuming that the fuel cell tram starts from platform A at an initial speed of 0 km / h, when it arrives at the crossroads, it is determined whether the tram stops according to the phase of the traffic light, wherein the tram must stop when the red light phase is red; during the driving process of the fuel cell tram, the fuel cell tram obtains the signal of the traffic light through the vehicle infrastructure interconnection system V2I.

[0059] Step 2: Establish a simple structural model and a dynamic model of the fuel cell tram, and construct inequality constraints of the dynamic model based on the maximum and minimum values ​​of the power data of the fuel cell power, power battery power, and motor power of the fuel cell tram and the dynamic model;

[0060] A simple structural model of a fuel cell tram Figure 2 As shown, its specific structure is: the fuel cell is connected to the bus through a unidirectional DC / DC converter; the power battery is connected to the bus, and a DC / AC converter is added to the bus to connect to the motor, and the fuel cell and the power battery are both connected to the motor to drive the motor together or individually;

[0061] The dynamic model of the fuel cell tram is expressed as:

[0062]

[0063]

[0064] Among them, F t represents the required traction of the fuel cell tram obtained according to the optimized speed sequence; P req (t) represents the total required power of the fuel cell tram calculated based on the required traction and vehicle speed; m represents the mass of the fuel cell tram, which is specifically 80 t in this embodiment; g represents the acceleration due to gravity, which is specifically 9.8 m / s in this embodiment 2 ; α represents the road angle; w0 represents the unit basic resistance; G d represents the total mass of the fuel cell tram including the rotating mass; v represents the speed of the fuel cell tram; η DC / AC Indicates the efficiency of the DC / AC converter; η M Indicates the efficiency of the motor; η T Indicates the transmission efficiency of the system; According to the simple structural model of the fuel cell tram, the power balance relationship of the fuel cell tram (the relationship between the total required power, fuel cell power and power battery power) is:

[0065] P req (t) = P fc (t)·η DC / DC +P bat (t)

[0066] Where P fc , P bat , η DC / DC They represent the fuel cell power, power battery power and efficiency of the DC / DC converter respectively.

[0067] Unit basic resistance w0 in the fuel cell tram dynamics model and the total mass G of the fuel cell tram including the rotating mass d Can be expressed as:

[0068]

[0069] Wherein a, b, c are resistance parameters respectively, v represents vehicle speed, γ represents rotational mass coefficient, a, b, c and γ are determined based on experience. In this embodiment, a is 2.59, b is 0.091, c is 0.000775, and γ represents rotational mass coefficient, and its value is 0.1.

[0070] According to the required traction force of the fuel cell tram, the total required power of the fuel cell tram can be obtained, which is specifically expressed as:

[0071]

[0072] According to the required power of the fuel cell tram, the power balance relationship of the fuel cell tram can be obtained:

[0073] P req (t) = P fc (t)·η DC / DC +P bat (t)

[0074] Where P fc , P bat , η DC / DC , η DC / AC , η M , η T They respectively represent the fuel cell power, the power battery power, the efficiency of the DC / DC converter, the efficiency of the DC / AC converter, the efficiency of the drive motor and the efficiency of the transmission system. For the convenience of calculation, the present invention takes the efficiency of the DC / AC converter, the DC / DC converter and the transmission system as 0.9, and the efficiency of the drive motor as 0.85.

[0075] The simple structural model of the fuel cell tram includes a fuel cell, a power battery and a motor. For the fuel cell, in order to simplify the calculation, the internal model of the fuel cell is not considered, only the power output of the fuel cell is considered, and the maximum and minimum power of the fuel cell are set as constraints; for the power battery, a simple equivalent battery model is used to express the internal state of the battery, and the relationship between the battery internal resistance and the open circuit voltage is expressed as:

[0076]

[0077] Wherein, OCV represents the open circuit voltage; bat Represents the circuit current, Rint Indicates the internal resistance of the battery; C bat represents the battery capacity; SOC0 represents the initial state of charge of the battery; SOC(t) represents the state of charge of the battery at each moment; for the motor, the influence of the motor transient response is not considered, and the motor efficiency is simplified to a function related to the motor speed and torque, which can be expressed as:

[0078] η M (ω MG ,T MG ) = f MG (ω MG ,T MG )

[0079] Where η M Represents the efficiency of the motor, ω MG Indicates the motor speed, T MG Represents the torque of the motor, f MG It represents the functional relationship between the motor speed torque and the motor efficiency. For the convenience of calculation, the motor efficiency is selected as a fixed value of 0.85.

[0080] The inequality constraints of the dynamic model are specifically expressed as:

[0081] P fc,min <P fc (t)<P fc,max

[0082] P bat,min <P bat (t)<P bat,max

[0083] P mot,min <P mot (t)<P mot,max

[0084] SOC min <SOC(t)<SOC max

[0085] Where P fc (t),P fc,min ,P fc,max Respectively represent the real-time power of the fuel cell and its minimum and maximum power; P bat (t),P bat,min ,P bat,max , respectively represent the real-time power of the power battery and its minimum and maximum power: P mot (t),P mot,min ,P mot,max , respectively represent the real-time power of the motor and its minimum and maximum power; SOC(t) represents the charge state of the battery at each moment, i.e. SOC, SOCmin Indicates the minimum value of the power battery SOC, SOC max Indicates the maximum value of the power battery SOC.

[0086] Step 3: The fuel cell tram obtains the distance between the fuel cell tram and the traffic light intersection and the traffic light phase with the help of the vehicle infrastructure interconnection system V2I, and uses the pseudo-spectral method to optimize the speed trajectory of the fuel cell tram; the specific process of using the pseudo-spectral method to optimize the speed trajectory of the fuel cell tram is as follows: according to the scene environment model established in step 1, combined with the dynamic model of the fuel cell tram and the traffic light phase information obtained by the vehicle infrastructure interconnection system V2I and the state information between the two stations, combined with the maximum speed, maximum and minimum acceleration, maximum and minimum braking force, and maximum and minimum traction of the fuel cell tram, the pseudo-spectral method is used to obtain the optimal speed sequence from station A to station B under the constraints, so as to optimize the speed trajectory of the fuel cell tram. The optimized speed trajectory is as follows: Figure 3 shown.

[0087] Step 4: Based on the optimized speed and the simple structural model and dynamic model of the fuel cell tram, calculate the required power P of the fuel cell tram req (t) and the power balance relationship of the fuel cell tram.

[0088] Step 5: According to the required power P of the fuel cell tram req (t), and P in the power balance equation fc and P bat , the SOC of the power battery is taken as the state variable, and the fuel cell power P fc As the control variable, and under the constraints of the dynamic model in step 2, the total energy consumption of tram operation is minimized as the optimization objective function J e , combined with state variables, control variables and optimization objective functions, the PSO algorithm is used to efficiently and reasonably allocate the required power of the fuel cell tram to the fuel cell and the power battery, realizing an energy management method with the goal of minimizing total energy consumption.

[0089] Among them, the optimization objective function J e The selection of the fuel cell hydrogen H2 consumption and the power battery equivalent H2 consumption is selected as the optimization objective function J e , specifically expressed as:

[0090]

[0091] In the formula, J e Represents the optimization objective function, that is, the total minimum energy consumption, where represents the hydrogen consumption rate of the fuel cell, represents the equivalent hydrogen consumption rate of the power battery, ξ represents the adjustment coefficient introduced into the optimization objective function, and the total minimum energy consumption is obtained by finding the minimum value of the integral of the two consumption rates, that is, the total energy consumption of the tram operation is minimized.

[0092] Furthermore, the objective function J is optimized e In The specific expressions of and ξ are as follows:

[0093]

[0094]

[0095]

[0096] Where P fc Represents the power of the fuel cell, P bat Indicates the power of the power battery, η fc represents the efficiency of the fuel cell, η DC / AC Indicates the efficiency of the DC / DC converter, LHV is the lower heating value of hydrogen, through the The specific expressions of and ξ are used, and the PSO algorithm is used to implement an energy management method with the goal of minimizing total energy consumption.

[0097] In order to verify the effectiveness of the present invention, a control group is set up in this specific embodiment. The control group adopts a fuel cell tram energy management method based on speed optimization and rules. According to the dynamic model and optimization objectives of the fuel cell tram, the state variables and objective function data of the control group are calculated to verify the present invention.

[0098] like Figure 4a , Figure 4b , Figure 5a , Figure 5b As shown in Figure 2, the changes in the power battery SOC, the hydrogen consumption of the fuel cell, the output power of the fuel cell and the power battery output power are compared between the tram energy management strategy based on speed optimization and rules and the tram energy management strategy based on speed optimization and PSO algorithm. Figure 5a and 5b It can be seen that the rule-based tram energy management strategy mainly uses power batteries as the energy source in the initial stage. Figure 4a As shown, SOC decreases rapidly, such as Figure 4b As shown in the figure, the H2 consumption at this time is lower than that of the tram energy management strategy based on the PSO algorithm. However, when the SOC drops to 0.3, in order to keep the SOC at this stable state, the rule-based tram energy management strategy uses the fuel cell as the main energy source and charges the power battery, as shown in the figure. Figure 4bAs shown in the figure, the H2 consumption at this time rises rapidly and exceeds the tram energy management strategy based on the PSO algorithm. After optimization by the PSO algorithm, the SOC of the fuel cell tram power battery decreases slowly, close to the optimal linear change trend, and the final H2 consumption is lower than the H2 consumption under the rule-based tram energy management strategy.

[0099] In summary, the energy optimization method based on speed optimization and PSO proposed in the present invention can more reasonably allocate the power of fuel cells and power batteries under the goal of minimizing the total energy consumption of fuel cell trams, and ultimately improve the economy of fuel cell trams by 3.72%.

[0100] The embodiments described above are only preferred implementation modes of the present invention and are not intended to limit the concept and scope of the present invention. Without departing from the design concept of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary engineering technicians in the field should fall within the protection scope of the present invention. The technical contents for which protection is requested in the present invention have been fully recorded in the technical requirements.

Claims

1. A fuel cell tram energy management method based on pseudo-spectrum and PSO algorithm, characterized by: The following steps are involved: Step 1: Establish a scene environment model of a fuel cell tram; Step 2: Establish a simple structural model and a dynamic model of a fuel cell tram. Based on the maximum and minimum values ​​of the power data of the fuel cell power, power battery power, and motor power of the fuel cell tram and the dynamic model, construct the inequality constraints of the dynamic model. The specific structure of the simple structural model of the fuel cell tram is as follows: the fuel cell is connected to the bus through a unidirectional DC / DC converter; the power battery is connected to the bus, and a DC / AC converter is added to the bus to connect to the motor. The fuel cell and the power battery are both connected to the motor to drive the motor together or individually. The dynamic model of the fuel cell tram is expressed as: Among them, F t (t) represents the traction force required during the operation of the fuel cell tram; P req (t) represents the required power of the fuel cell tram according to the required traction and vehicle speed; m represents the mass of the fuel cell tram, g represents the acceleration of gravity; α represents the road angle; w0 represents the unit basic resistance; G d represents the total mass of the fuel cell tram including the rotating mass; v represents the speed of the fuel cell tram; h DC / AC Indicates the efficiency of the DC / AC converter; h M Indicates the efficiency of the motor; h T Represents the transmission efficiency of the system; according to the simple structural model of the fuel cell tram, the power balance relationship of the fuel cell tram is: P req (t)=P fc (t)×h DC / DC +P bat (t) Where P fc , P bat 、h DC / DC They represent the fuel cell power, power battery power and efficiency of the DC / DC converter respectively; Unit basic resistance w0 in the fuel cell tram dynamics model and the total mass G of the fuel cell tram including the rotating mass d Can be expressed as: Where a, b, c are resistance parameters, v represents vehicle speed, and γ represents the rotational mass coefficient; The simple structural model of the fuel cell tram includes a fuel cell, a power battery and a motor. For the fuel cell, in order to simplify the calculation, the internal model of the fuel cell is not considered, only the power output of the fuel cell is considered, and the maximum and minimum power of the fuel cell are set as constraints; for the power battery, a simple and effective equivalent battery model is used to express the internal state of the battery, and the relationship between the battery internal resistance and the open circuit voltage is expressed as: Wherein, OCV represents the open circuit voltage; i bat Represents the circuit current, R int Indicates the internal resistance of the battery; C bat represents the battery capacity; SOC0 represents the initial state of charge of the battery; SOC(t) represents the state of charge of the battery at each moment; for the motor, the influence of the motor transient response is not considered, and the motor efficiency is simplified to a function related to the motor speed and torque, which can be expressed as: h M (ω MG ,T MG )=f MG (ω MG ,T MG ) In the formula, h M Represents the efficiency of the motor, ω MG Indicates the motor speed, T MG Represents the torque of the motor, f MG It represents the functional relationship between the motor speed torque and motor efficiency; The inequality constraints for constructing the dynamic model in step 2 are specifically expressed as: P fc,min <P fc (t)<P fc,max P bat,min <P bat (t)<P bat,max P mot,min <P mot (t)<P mot,max SOC min <SOC(t)<SOC max Where P fc (t),P fc,min ,P fc,max Respectively represent the real-time power of the fuel cell and its minimum and maximum power; P bat (t),P bat,min ,P bat,max , respectively represent the real-time power of the power battery and its minimum and maximum power: P mot (t),P mot,min ,P mot,max , respectively represent the real-time power of the motor and its minimum and maximum power; SOC(t) represents the charge state of the battery at each moment, i.e. SOC, SOC min Indicates the minimum value of the power battery SOC, SOC max Indicates the maximum value of the power battery SOC; Step 3: The fuel cell tram obtains the distance between the fuel cell tram and the traffic light intersection and the traffic light phase with the help of the vehicle infrastructure interconnection system V2I, and optimizes the speed trajectory of the fuel cell tram using the pseudo-spectral method; Step 4: Based on the optimized speed and the simple structural model and dynamic model of the fuel cell tram, calculate the required power P of the fuel cell tram req (t) and the power balance relationship of the fuel cell tram; Step 5: According to the required power of the fuel cell tram, the SOC of the power battery is used as the state variable, the fuel cell power is used as the control variable, and the minimum total energy consumption of the tram operation is used as the optimization objective function J e , under the constraints of the dynamic model in step 2, the particle swarm algorithm PSO is used to allocate the required power of the fuel cell tram, and the required power is efficiently and reasonably allocated to the fuel cell and the power battery to perform energy management of the fuel cell tram; Optimize the objective function J e The selection of the fuel cell hydrogen H2 consumption and the power battery equivalent H2 consumption is selected as the optimization objective function J e , specifically expressed as: In the formula, J e Represents the optimization objective function, that is, the total minimum energy consumption, where represents the hydrogen consumption rate of the fuel cell, represents the equivalent hydrogen consumption rate of the power battery, and ξ represents the adjustment coefficient introduced into the optimization objective function.

2. The fuel cell tram energy management method based on pseudo spectrum and PSO algorithm according to claim 1 is characterized by: The scene environment model of the fuel cell tram established in the step 1 is specifically as follows: on a certain city road, two adjacent tram stations are set as A and B, station A is the starting station, station B is the ending station, and a crossroads with a traffic light is set between station A and station B, and the distance between the traffic light and station A is S1, and the distance between the traffic light and station B is S2; assuming that the fuel cell tram starts from station A at an initial speed v0, when it arrives at the crossroads, it is determined whether the tram stops according to the phase of the traffic light, wherein the tram must stop when the red light phase is red; during the driving process of the fuel cell tram, the fuel cell tram obtains the signal of the traffic light through the vehicle infrastructure interconnection system V2I.

3. The fuel cell tram energy management method based on pseudo-spectrum and PSO algorithm according to claim 1 is characterized by: The specific process of using the pseudo-spectral method to optimize the speed trajectory of the fuel cell tram in step 3 is as follows: according to the scene environment model established in step 1, combined with the dynamic model of the fuel cell tram and the traffic light phase information obtained by the vehicle infrastructure interconnection system V2I and the state information between the two stations, combined with the maximum speed, maximum and minimum acceleration, maximum and minimum braking force, and maximum and minimum traction of the fuel cell tram, the pseudo-spectral method is used to obtain the optimal speed sequence from station A to station B under constraints, so that the fuel cell tram can pass through the traffic light intersection without stopping, thereby optimizing the speed trajectory of the fuel cell tram.

4. The method for energy management of a fuel cell tram based on pseudo-spectrum and PSO algorithm according to claim 1 is characterized in that: Optimize the objective function J e In The specific expressions of and ξ are as follows: Where P fc (t) represents the real-time power of the fuel cell, P bat (t) represents the real-time power of the power battery, h fc represents the efficiency of the fuel cell, h DC / AC Indicates the efficiency of the DC / DC converter, and LHV stands for the lower heating value of hydrogen.

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