Vehicle-mounted hybrid energy storage system energy control method and system

Abstract

The present application relates to the technical field of urban rail transit energy storage, and discloses a vehicle-mounted hybrid energy storage system energy control method and system, which calculates the output power of a train traction motor, establishes the relationship between the state of charge and the terminal voltage of a super capacitor group and the state of charge and the current of a storage battery group, constructs a fuzzy quantizer, a fuzzy inference engine and a fuzzy rule updater of the super capacitor group and the storage battery group, constructs a voltage outer loop PI controller and a current inner loop PI controller with a dead zone for the super capacitor group and the storage battery group, and obtains a control signal of a bidirectional DC / DC converter to maintain the stability of a DC bus voltage and improve the energy saving rate.

Description

Technical Field

[0001] The present invention relates to the field of urban rail transit energy storage technology, and in particular to an energy control method and system for an on-board hybrid energy storage system. Background Art

[0002] In the urban rail transit sector, with the acceleration of urbanization and increasing transportation demands, the demand for efficient, reliable, and energy-efficient electric traction systems is growing. Onboard hybrid energy storage systems, a key technology for improving the energy efficiency of rail transit vehicles, effectively support stable system operation and optimized energy utilization through intelligent energy flow management.

[0003] Existing energy control methods for on-board hybrid energy storage systems often employ rule-based control strategies, which often lack a deep understanding of and predictive capabilities for the system's dynamic characteristics. Furthermore, due to complex and volatile operating environments, existing technologies remain inadequate in maintaining DC bus voltage stability and improving energy savings, hindering the system's full energy-saving potential. Summary of the Invention

[0004] The present invention provides an energy control method and system for a vehicle-mounted hybrid energy storage system, so as to solve the problem that the vehicle-mounted hybrid energy storage system in the prior art still has deficiencies in maintaining DC bus voltage stability and improving energy saving rate.

[0005] In order to achieve the above object, the present invention is implemented through the following technical solutions:

[0006] In a first aspect, the present invention provides an energy control method for a vehicle-mounted hybrid energy storage system, comprising:

[0007] S1: Obtain parameter information of the traction motor of the target train, and calculate the output power of the traction motor of the train based on the parameter information;

[0008] S2: Establish the relationship between the state of charge of the supercapacitor group and the terminal voltage, and the relationship between the state of charge of the battery group and the current;

[0009] S3: constructing a fuzzy quantizer for the supercapacitor group and the battery group based on the output power of the train traction motor, the DC bus voltage, the state of charge of the supercapacitor group, and the state of charge of the battery group; constructing a fuzzy reasoner for the supercapacitor group and the battery group based on the output information of the fuzzy quantizer for the supercapacitor group and the battery group; and constructing a fuzzy rule updater for the supercapacitor group and the battery group based on the output information of the fuzzy reasoner for the supercapacitor group and the battery group;

[0010] S4: setting a dead zone size based on the fuzzy rule updater to obtain a dead zone function, and constructing a voltage outer loop PI controller and a current inner loop PI controller with dead zones for the supercapacitor group and the battery group respectively based on the dead zone function;

[0011] S5: Based on the voltage outer loop PI controller and current inner loop PI controller with dead zone of the supercapacitor group and the battery group, a control signal of the bidirectional DC / DC converter is obtained to control the energy of the vehicle-mounted hybrid energy storage system.

[0012] In a second aspect, the present application provides an energy control system for a vehicle-mounted hybrid energy storage system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method described in the first aspect are implemented.

[0013] Beneficial effects:

[0014] This application provides an energy control method for an on-board hybrid energy storage system, including the real-time energy state of the energy storage system, the DC bus voltage state, and the vehicle power state. This method is applicable to the variable operating conditions of complex practical systems. Fuzzy rules are used to generate energy control strategies, improving the robustness of the system. The dynamic performance of the system is improved by updating the fuzzy rules. By controlling the energy of the hybrid energy storage system, the charging and discharging processes of the energy storage units are optimized, energy losses are reduced, and the energy utilization efficiency of the system is improved. The DC bus voltage is maintained stable, reducing the impact of voltage fluctuations on the electric traction system, thereby enhancing the stability and reliability of the entire system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0016] Figure 1 This is a flow chart of an energy control method for a vehicle-mounted hybrid energy storage system according to a preferred embodiment of the present invention;

[0017] Figure 2 1 is a topological diagram of an energy control method for a vehicle-mounted hybrid energy storage system according to a preferred embodiment of the present invention;

[0018] Figure 3 This is a block diagram of the overall structure of the energy control method of the vehicle-mounted hybrid energy storage system according to the preferred embodiment of the present invention;

[0019] Figure 4 Schematic diagram of the operating conditions of the energy control method of the vehicle-mounted hybrid energy storage system according to the preferred embodiment of the present invention;

[0020] Figure 5This is a membership function diagram of a supercapacitor group of a vehicle-mounted hybrid energy storage system according to a preferred embodiment of the present invention;

[0021] Figure 6 This is a membership function diagram of a battery pack of a vehicle-mounted hybrid energy storage system according to a preferred embodiment of the present invention;

[0022] Figure 7 This is a DC bus voltage comparison diagram of the energy control method for a vehicle-mounted hybrid energy storage system according to a preferred embodiment of the present invention;

[0023] Figure 8 This is a DC bus power comparison diagram of the energy control method for a vehicle-mounted hybrid energy storage system according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following is a clear and complete description of the technical solutions of the present invention. It is obvious that the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0025] Unless otherwise defined, the technical or scientific terms used in the present invention shall have the usual meanings understood by persons of ordinary skill in the field to which the present invention belongs. The words "first", "second" and similar terms used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one" or "a" do not indicate a quantity limitation, but rather indicate the existence of at least one. Words such as "connected" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship also changes accordingly.

[0026] See Figure 1 , the present application provides an energy control method for a vehicle-mounted hybrid energy storage system, comprising:

[0027] S1: Obtain parameter information of the traction motor of the target train, and calculate the output power of the traction motor of the train based on the parameter information;

[0028] S2: Establish the relationship between the state of charge of the supercapacitor group and the terminal voltage, and the relationship between the state of charge of the battery group and the current;

[0029] It is worth mentioning that the energy control of the hybrid energy storage system needs to know the current energy level of each energy storage group, which is usually not measurable by a suitable sensor. The state of charge (SOC) is used to describe the ratio of the current remaining capacity of the battery to its fully charged state capacity during the use of the battery, and is usually used to reflect the current energy level of the energy storage group. For the super capacitor group, the relationship between the state of charge of the super capacitor group and the terminal voltage is established, and the current state of charge can be obtained through the measurable terminal voltage; for the battery group, the relationship between the state of charge of the battery group and the current is established from the state of charge mechanism, and the state of charge up to the current time period is obtained by using current integration through the measurable current.

[0030] S3: Constructing a fuzzy quantizer of the super capacitor group and the battery group based on the train traction motor output power, the DC bus voltage, the state of charge of the super capacitor group and the state of charge of the battery group, constructing a fuzzy inference engine of the super capacitor group and the battery group based on the output information of the fuzzy quantizer of the super capacitor group and the battery group, and constructing a fuzzy rule updater of the super capacitor group and the battery group based on the output information of the fuzzy inference engine of the super capacitor group and the battery group;

[0031] S4: Setting a dead zone size based on the fuzzy rule updater to obtain a dead zone function, and respectively constructing a voltage outer loop PI controller and a current inner loop PI controller of the super capacitor group and the battery group with a dead zone based on the dead zone function;

[0032] S5: Obtaining the control signal of the bidirectional DC / DC converter based on the voltage outer loop PI controller and the current inner loop PI controller of the super capacitor group and the battery group with a dead zone, and controlling the energy of the on-board hybrid energy storage system.

[0033] The above-mentioned on-board hybrid energy storage system energy control method can realize effective utilization of the energy in the hybrid energy storage system. The method can be applied to complex actual system variable working condition factors, and can effectively utilize the energy in the energy storage system under different vehicle energy demands, different operating conditions and operating loads. The method generates an energy control strategy using fuzzy rules, which improves the robustness of the system; and the dynamic performance of the system is improved by updating the fuzzy rules. Through energy control of the hybrid energy storage system, the charging and discharging process of the energy storage unit is optimized, energy loss is reduced, and the energy utilization efficiency of the system is improved. The stability of the DC bus voltage is maintained, the influence of voltage fluctuation on the electric traction system is reduced, and the stability and reliability of the entire system are enhanced.

[0034] In the following, the steps of the above-mentioned method are described in detail in a complete embodiment.

[0035] 1. Please refer to Figure 2 and Figure 3 , calculate the output power of the train traction motor.

[0036] Step 1: Calculate the output power of the train traction motor, satisfying the following relationship:

[0037] P out =T e ω motor η;

[0038] Among them, P out is the output power of the train traction motor, T e is the electromagnetic torque of the traction motor, ω motor is the motor angular velocity, η is the motor efficiency constant;

[0039] 2. Establish the relationship between the state of charge of the supercapacitor group and the terminal voltage, and the state of charge of the battery group and the current respectively.

[0040] Step 1: Establish the relationship between the state of charge of the supercapacitor group and the terminal voltage of the supercapacitor group, which satisfies the following relationship:

[0041]

[0042] Among them, SOC SC is the state of charge of the supercapacitor bank, U SC_t is the current terminal voltage of the supercapacitor group, U SC_N is the rated terminal voltage of the supercapacitor bank.

[0043] Step 2: Establish the relationship between the battery pack state of charge and the battery pack current, satisfying the following relationship:

[0044]

[0045] Among them, SOC bat SOC is the state of charge of the battery pack bat_0 is the initial state of charge of the battery pack, i(τ) is the battery pack current, Q bat_N Rated capacity of the battery pack.

[0046] 3. Construct the fuzzy quantizer, fuzzy reasoner, and fuzzy rule updater for the supercapacitor group and battery group respectively.

[0047] Step 1: Construct a fuzzy quantizer for the supercapacitor group.

[0048] The inputs of the supercapacitor bank fuzzy quantizer are the DC bus voltage U dc , Supercapacitor bank state of charge SOC SC and the train traction motor output power P out, respectively divided into ε, δ, γ fuzzy centers; the supercapacitor group fuzzy quantizer outputs are corresponding to the current input U dc , SOC SC 、P out The membership matrix represents the real number domain, the number of matrix elements is the same as the fuzzy center number ε, δ, and γ, and the membership matrix satisfies the following relationship:

[0049]

[0050] Among them, φ SC_1 (U dc ), φ SC_2 (SOC SC ), φ SC_3 (P out ), is a continuous function, and a1, a2, a3, b1, b2, b3, c1, c2, c3 are constants.

[0051] Specifically, commonly used membership functions include linear, bell-shaped (e.g., Gaussian function), S-shaped, Z-shaped, trapezoidal, and other forms. The specific form depends on which membership function the system works better under, and is usually selected by experimental methods. In the embodiments of this patent, triangular and linear membership functions are selected as continuous functions.

[0052] Step 2: Construct a battery pack fuzzy quantizer.

[0053] The inputs of the battery pack fuzzy quantizer are the DC bus voltage U dc , battery pack state of charge SOC bat and the train traction motor output power P out , respectively divided into λ, α, β fuzzy centers; the battery pack fuzzy quantizer outputs are corresponding to the current input U dc , SOC bat 、P out The membership matrix The number of matrix elements is the same as the number of fuzzy centers λ, α, and β, and the membership matrix satisfies the following relationship:

[0054]

[0055] Among them, φ bat_1 (U dc ), φ bat_2 (SOC bat ), φ bat_3 (P out), is a continuous function, and a4, a5, a6, b4, b5, b6, c4, c5, c6 are constants.

[0056] Step 3: Construct a fuzzy reasoner for the supercapacitor group.

[0057] The inputs of the supercapacitor group fuzzy inference device are the membership matrix μ output by the supercapacitor group fuzzy quantizer and SC (U dc ), μ SC (SOC sc ), μ SC (P out ); The output of the supercapacitor bank fuzzy inference is the supercapacitor bank charge and discharge threshold value U th_SC ;

[0058] Step 4: Construct a battery pack fuzzy reasoner.

[0059] The inputs of the battery pack fuzzy inference unit are the membership matrix μ output by the battery pack fuzzy quantizer and bat (SOC bat ), μ bat (U dc ), μ bat (P out ); the output of the battery pack fuzzy inference device is the battery pack charge and discharge threshold value U th_bat ;

[0060] Step 5: Use the maximum and minimum reasoning to solve the charge and discharge thresholds of the supercapacitor group and the battery group for the first The membership degree of the ρ fuzzy centers satisfies the following relationship:

[0061]

[0062] in, The charge and discharge thresholds of the supercapacitor group and the battery group are The membership degree of ρ fuzzy centers, ρ=1,2,…,Υ;∨ means taking the maximum value, ∧ means taking the minimum value, U, S, P are the DC bus voltage U dc , energy storage device state of charge SOC, traction motor output power P out The domain of discourse, R is the composite fuzzy relation on U×S, M is the composite fuzzy relation on S×P, T is the composite fuzzy relation on U×P, Q is the inference result, Respectively represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on U×S, Respectively represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on S×P, They represent the composite fuzzy relation membership of the supercapacitor bank and the battery bank on U×P, respectively. The “×” symbol is a special operator that represents the fuzzy product operation in the composite fuzzy relation operation and is a type of composite fuzzy relation set synthesis operation.

[0063] The composite fuzzy relationship membership satisfies the following relationship:

[0064]

[0065] Where, Indicates that in all membership In the value selection, the maximum value calculated in [·] is returned; Indicates that among all the values ​​of membership ρ, the value with the largest calculated value in [·] is returned;

[0066] The weighted average method is used for defuzzification to obtain the charge and discharge thresholds of the supercapacitor group and the battery group, which satisfy the following relationship:

[0067]

[0068]

[0069] Among them, U th_SC 、U th_bat They are the charge and discharge thresholds of the supercapacitor group and the battery group respectively; u ρ_bat They are respectively the fuzzy set of charge and discharge thresholds of supercapacitor group and battery group. ρ fuzzy centers, ρ=1,2,…,Υ。

[0070] Fuzzy set of charge and discharge thresholds of supercapacitor and battery packs ρ fuzzy centers satisfy the following relationship:

[0071]

[0072] Among them, U dc_max 、U dc_min They represent the maximum and minimum values ​​of the allowable fluctuation of the DC bus voltage respectively.

[0073] Step 6: Construct fuzzy rule updaters for supercapacitor group and battery group respectively.

[0074] The input of the fuzzy rule updater is the deviation Δu and the deviation change rate Δu′ between the charge and discharge threshold output by the fuzzy inference device and the DC bus voltage, and the output is the rule reorganization update level. In the early stage of the train startup process, the DC bus voltage will drop rapidly. At this time, Δu and Δu′ will increase. At this time, the energy storage device needs to quickly enter the discharge state and release energy. Lowering the discharge threshold can achieve this goal. In the later stage of the train startup, the train is about to enter the uniform speed state. At this time, Δu decreases and the sign of Δu′ becomes negative. At this time, the discharge rate of the energy storage device can be slowed down to prepare for entering the standby state. At this time, the original strategy or slightly increasing the discharge threshold can achieve this goal. When the train brakes, Δu and Δu′ will increase but with the opposite sign to when the train starts. At this time, the energy storage device needs to quickly enter the charging state and absorb energy. Lowering the charging threshold can achieve this goal. In the later stage of the train braking, Δu decreases and the sign of Δu′ becomes positive. Only the energy storage device needs to absorb the residual energy.

[0075] The input of the supercapacitor bank fuzzy rule updater is the charge and discharge threshold U output by the supercapacitor bank fuzzy reasoner. th_SC The deviation Δu between the DC bus voltage, the deviation change rate Δu′ and the current supercapacitor group charge and discharge threshold division level ω; the fuzzy rule updater outputs the supercapacitor group charge and discharge threshold division level after the fuzzy rule update.

[0076] After the fuzzy rules are updated, the supercapacitor bank charge and discharge thresholds are divided into levels, satisfying the following relationship:

[0077]

[0078] Where ω′ represents the division level of the supercapacitor bank charge and discharge threshold after the fuzzy rule is updated, ω′=1,2,…,Ω′, ω represents the division level of the current supercapacitor bank charge and discharge threshold, ω=1,2,…,Ω, Δu is the charge and discharge threshold U output by the fuzzy inference controller of the battery bank th_bat The deviation between the DC bus voltage and the Δu′ is the charge and discharge threshold U output by the fuzzy inference device of the battery pack. th_bat The rate of change of the deviation from the DC bus voltage, f SC (Δu, Δu′) is the update rule of the supercapacitor group fuzzy rule base regarding Δu and Δu′, which satisfies the following relationship:

[0079]

[0080] Among them, + and - respectively represent the division levels of increasing and decreasing the charge and discharge thresholds, p SC ,q SC Respectively represent the value of increasing and decreasing the supercapacitor group charge and discharge threshold division level, p SC =1,2,3,…,P SC ,q SC= 1, 2, 3,..., Q SC , and p SC > q SC , a SC , b SC , c SC are constants.

[0081] The battery pack fuzzy rule updater inputs the deviation Δu between the charge-discharge threshold value U th_bat and the DC bus voltage, the deviation change rate Δu', and the current battery pack charge-discharge threshold value division level ξ, and outputs the battery pack charge-discharge threshold value division level after fuzzy rule updating.

[0082] The battery pack charge-discharge threshold value division level after fuzzy rule updating satisfies the following relationship:

[0083]

[0084] In the formula, ξ' represents the battery pack charge-discharge threshold value division level after fuzzy rule updating, ξ' = 1, 2,..., Ξ', ξ represents the current battery pack charge-discharge threshold value division level, ξ = 1, 2,..., Ξ; f bat (Δu, Δu') is the updating rule of the battery pack fuzzy rule base about Δu and Δu', which satisfies the following relationship:

[0085]

[0086] In the formula, p bat , q bat represent the values of increasing and decreasing the battery pack charge-discharge threshold value division level, p bat = 1, 2, 3,..., P bat , q bat = 1, 2, 3,..., Q bat , and p bat > q bat , a bat , b bat , c bat are constants.

[0087] 4. Please refer to Figure 3 , respectively, to construct the voltage outer loop PI controller with dead zone of the super capacitor group and the current inner loop PI controller of the battery pack, specifically:

[0088] The voltage outer loop PI controller with dead zone of the super capacitor group is constructed, and the dead zone size is set to: [-v SC , +v SC ], and the dead zone function satisfies the following relationship:

[0089]

[0090] Among them, u SC It is the signal input to the supercapacitor group voltage outer loop controller;

[0091] The voltage outer loop PI controller formula of the supercapacitor bank with dead zone is:

[0092]

[0093] Among them, out_i SC (t) is the output signal of the voltage outer loop PI controller with dead zone of the supercapacitor group, K SC_u_p is the control gain of the supercapacitor bank voltage outer loop PI controller, T SC_u_i is the integral time constant of the supercapacitor bank voltage outer loop PI controller;

[0094] Construct a voltage outer loop PI controller with dead zone for the battery pack, and set the dead zone size to: [-v bat , +v bat ], the dead zone function satisfies the following relationship:

[0095]

[0096] Among them, u bat It is the signal input to the battery pack voltage outer loop controller;

[0097] The battery pack voltage outer loop PI controller with dead zone satisfies the following relationship:

[0098]

[0099] Among them, out_i bat (t) is the output signal of the voltage outer loop PI controller with dead zone for the battery pack, K bat_u_p is the control gain of the battery pack voltage outer loop PI controller, T bat_u_i is the integral time constant of the battery pack voltage outer loop PI controller;

[0100] Construct the inner loop PI controller of the supercapacitor bank current to satisfy the following relationship:

[0101]

[0102] Among them, out_d SC (t) is the output signal of the inner loop PI controller of the supercapacitor group current, e SC (i) is the input signal of the supercapacitor bank current inner loop PI controller, which is also the current deviation value, K SC_i_p is the control gain of the supercapacitor bank current inner loop PI controller, T SC_i_iis the integral time constant of the inner loop PI controller of the supercapacitor bank current;

[0103] Construct the battery pack current inner loop PI controller, the formula is:

[0104]

[0105] Among them, out_d bat (t) is the output signal of the inner loop PI controller of the battery pack current, e bat (i) is the input signal of the battery pack current inner loop PI controller, which is also the current deviation value, K bat_i_p is the control gain of the battery pack current inner loop PI controller, T bat_i_i is the integral time constant of the battery pack current inner loop PI controller.

[0106] The above formula constitutes the energy control method of the on-board hybrid energy storage system.

[0107] The urban rail transit system in the above embodiment is a DC bus voltage 1500V power supply system, the maximum vehicle speed is 120Km / h, and the DC bus voltage fluctuation range is allowed to be: 1000V-1800V. Figure 4 The membership function of the supercapacitor group and the battery group is shown as Figure 5 、 Figure 6 The experimental parameters are shown in Table 1. The initial charging fuzzy rules of the supercapacitor group and the battery group are shown in Table 2 and Table 3, and the initial discharging fuzzy rules of the supercapacitor group and the battery group are shown in Table 4 and Table 5.

[0108] Table 1

[0109]

[0110]

[0111] Table 2

[0112]

[0113] Table 3

[0114]

[0115] Table 4

[0116]

[0117]

[0118] Table 5

[0119]

[0120] Among them, during the operation of the train, the DC bus voltage fluctuations under three conditions: no hybrid energy storage system, traditional energy control method of hybrid energy storage system and energy control method of on-board hybrid energy storage system invented are as follows: Figure 7 As shown, the traction network power required by the train is as follows Figure 8 As shown, the provided method can better maintain the stability of the DC bus voltage, reduce the power provided by the traction network, and improve the energy saving rate compared with the previous method.

[0121] The present application also provides an on-board hybrid energy storage system energy control system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-described method are implemented. This on-board hybrid energy storage system energy control system can implement various embodiments of the above-described method and achieve the same beneficial effects, which are not further described here.

[0122] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A method for controlling energy of a vehicle-mounted hybrid energy storage system, characterized in that: include: S1: Obtain parameter information of the target train traction motor, and calculate the output power of the train traction motor based on the parameter information; S2: Establish the relationship between the state of charge of the supercapacitor group and the terminal voltage, and the relationship between the state of charge of the battery group and the current; S3: constructing a fuzzy quantizer for the supercapacitor group and the battery group based on the output power of the train traction motor, the DC bus voltage, the state of charge of the supercapacitor group, and the state of charge of the battery group; constructing a fuzzy reasoner for the supercapacitor group and the battery group based on the output information of the fuzzy quantizer for the supercapacitor group and the battery group; and constructing a fuzzy rule updater for the supercapacitor group and the battery group based on the output information of the fuzzy reasoner for the supercapacitor group and the battery group; S4: setting a dead zone size based on the fuzzy rule updater to obtain a dead zone function, and constructing a voltage outer loop PI controller and a current inner loop PI controller with dead zones for the supercapacitor group and the battery group respectively based on the dead zone function; S5: Based on the voltage outer loop PI controller and current inner loop PI controller with dead zone of the supercapacitor group and the battery group, a control signal of the bidirectional DC / DC converter is obtained to control the energy of the vehicle hybrid energy storage system; The S3 includes: S31: constructing a fuzzy quantizer for the supercapacitor group and a fuzzy quantizer for the battery group respectively; S32: constructing a fuzzy inference machine for the supercapacitor group and a fuzzy inference machine for the battery group respectively; S33: Construct a fuzzy rule updater for the supercapacitor group and a fuzzy rule updater for the battery group respectively.

2. The energy control method of a vehicle-mounted hybrid energy storage system according to claim 1, characterized in that: The parameter information of the traction motor of the target train includes: the electromagnetic torque and angular velocity of the traction motor; S1 includes: S11: Calculate the output power of the train traction motor, satisfying the following relationship: P out =T e oh motor or; Among them, P out is the output power of the train traction motor, T e is the electromagnetic torque of the traction motor, ω motor is the motor angular velocity, and η is the motor efficiency constant.

3. The energy control method of a vehicle-mounted hybrid energy storage system according to claim 1, characterized in that: The S2 includes: S21: Establish the relationship between the state of charge of the supercapacitor bank and the terminal voltage, which satisfies the following relationship: Among them, SOC SC is the state of charge of the supercapacitor bank, U SC_t is the current terminal voltage of the supercapacitor group, U SC_N is the rated terminal voltage of the supercapacitor bank; S22: Establish the relationship between the battery pack state of charge and current, satisfying the following relationship: Among them, SOC bat SOC is the state of charge of the battery pack bat_0 is the initial state of charge of the battery pack, i(τ) is the battery pack current, Q bat_N Rated capacity of the battery pack.

4. The energy control method of a vehicle-mounted hybrid energy storage system according to claim 1, characterized in that: The S31 includes: The inputs of the supercapacitor bank fuzzy quantizer are the DC bus voltage U dc , Supercapacitor bank state of charge SOC SC and the train traction motor output power P out , respectively divided into ε, δ, γ fuzzy centers, the supercapacitor group fuzzy quantizer outputs are corresponding to the current input U dc , SOC SC 、P out The membership matrix represents the real number domain, the number of matrix elements is the same as the fuzzy center number ε, δ, and γ, and the membership matrix satisfies the following relationship: φ SC_1 (U dc ), φ SC_2 (SOC SC ), φ SC_3 (P out ), represents a continuous function, where a1, a2, a3, b1, b2, b3, c1, c2, c3 are constants; The inputs of the battery pack fuzzy quantizer are the DC bus voltage U dc , battery pack state of charge SOC bat and the train traction motor output power P out , respectively divided into λ, α, β fuzzy centers, the battery pack fuzzy quantizer outputs are corresponding to the current input U dc , SOC bat 、P out The membership matrix The number of matrix elements is the same as the number of fuzzy centers λ, α, and β, and the membership matrix satisfies the following relationship: φ bat_1 (U dc ), φ bat_2 (SOC bat ), φ bat_3 (P out ), is a continuous function, a4, a5, a6, b4, b5, b6, c4, c5, c6 are constants; The S32 includes: the supercapacitor group fuzzy inference device inputs are the membership matrix μ output by the supercapacitor group fuzzy quantizer SC (U dc ), μ SC (SOC sc ), μ SC (P out ), the supercapacitor bank fuzzy inference output is the supercapacitor bank charge and discharge threshold value U th_SC ; The inputs of the battery pack fuzzy inference unit are the membership matrix μ output by the battery pack fuzzy quantizer and bat (SOC bat ), μ bat (U dc ), μ bat (P out ), the output of the battery pack fuzzy inference is the battery pack charge and discharge threshold value U th_bat ; Using the maximum and minimum reasoning, solve the charge and discharge thresholds of the supercapacitor group and the battery group for the The membership degree of the ρ fuzzy centers satisfies the following relationship: in, The charge and discharge thresholds of the supercapacitor group and the battery group are The membership degree of ρ fuzzy centers, ρ=1,2,…,Υ, ∨ means taking the maximum, ∧ means taking the minimum, U, S, P are the DC bus voltage U dc , energy storage device state of charge SOC, traction motor output power P out The domain of discourse, R is the composite fuzzy relation on U×S, M is the composite fuzzy relation on S×P, T is the composite fuzzy relation on U×P, Q is the inference result, Respectively represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on U×S, Respectively represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on S×P, Respectively represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on U×P; The composite fuzzy relationship membership satisfies the following relationship: Where, Indicates that in all membership In the value selection, the maximum value calculated in [·] is returned; Indicates that among all the values ​​of membership ρ, the value with the largest calculated value in [·] is returned; The weighted average method is used for defuzzification to obtain the charge and discharge thresholds of the supercapacitor group and the battery group, which satisfy the following relationship: Among them, U th_SC 、U th_bat They are respectively the charge and discharge thresholds of the supercapacitor group and the battery group, u ρ_bat They are respectively the fuzzy set of charge and discharge thresholds of supercapacitor group and battery group. ρ fuzzy centers, ρ=1,2,…,Υ; Fuzzy set of charge and discharge thresholds of supercapacitor and battery packs ρ fuzzy centers satisfy the following relationship: Among them, U dc_max 、U dc_min Respectively represent the maximum and minimum values ​​of the allowable fluctuation of the DC bus voltage; The S33 includes: the supercapacitor group fuzzy rule updater input is the charge and discharge threshold value U output by the supercapacitor group fuzzy reasoner th_SC The deviation Δu between the DC bus voltage, the deviation change rate Δu′ and the current supercapacitor group charge and discharge threshold division level ω, the fuzzy rule updater outputs the supercapacitor group charge and discharge threshold division level after the fuzzy rule update; After the fuzzy rules are updated, the supercapacitor bank charge and discharge thresholds are divided into levels, satisfying the following relationship: Where ω′ represents the division level of the supercapacitor bank charge and discharge threshold after the fuzzy rule is updated, ω′=1,2,…,Ω′, ω represents the division level of the current supercapacitor bank charge and discharge threshold, ω=1,2,…,Ω, Δu is the charge and discharge threshold U output by the fuzzy inference controller of the battery bank th_bat The deviation between the DC bus voltage and the Δu′ is the charge and discharge threshold U output by the fuzzy inference device of the battery pack. th_bat The rate of change of the deviation from the DC bus voltage, f SC (Δu, Δu′) is the update rule of the supercapacitor group fuzzy rule base regarding Δu and Δu′, which satisfies the following relationship: Among them, + and - respectively represent the division levels of increasing and decreasing the charge and discharge thresholds, p SC ,q SC Respectively represent the value of increasing and decreasing the supercapacitor group charge and discharge threshold division level, p SC =1,2,3,…,P SC ,q SC =1,2,3,…,Q SC , and p SC >q SC , a SC ,b SC ,c SC is a constant; The input of the battery pack fuzzy rule updater is the charge and discharge threshold value U output by the battery pack fuzzy inference unit. th_bat The deviation Δu between the DC bus voltage and the deviation change rate Δu′ and the current battery pack charge and discharge threshold classification level ξ, the fuzzy rule updater outputs the battery pack charge and discharge threshold classification level after the fuzzy rule update; After the fuzzy rules are updated, the battery pack charge and discharge thresholds are divided into levels, satisfying the following relationship: Where, ξ′ represents the division level of the battery pack charge and discharge threshold after the fuzzy rule is updated, ξ′=1,2,…,Ξ′, ξ represents the division level of the current battery pack charge and discharge threshold, ξ=1,2,…,Ξ, f bat (Δu, Δu′) is the update rule of the battery pack fuzzy rule base regarding Δu and Δu′, which satisfies the following relationship: Among them, p bat ,q bat Indicates the value of increasing or decreasing the charge and discharge threshold value of the battery pack. bat =1,2,3,…,P bat ,q bat =1,2,3,…,Q bat , and p bat >q bat , a bat ,b bat ,c bat is a constant.

5. The energy control method of a vehicle-mounted hybrid energy storage system according to claim 1, characterized in that: The S4 includes: S41: construct a voltage outer loop PI controller for the supercapacitor group and a voltage outer loop PI controller with dead zone for the battery group; Construct a voltage outer loop PI controller with dead zone for the supercapacitor group and set the dead zone size to: [-v SC , +v SC ], the dead zone function satisfies the following relationship: Among them, u SC It is the signal input to the supercapacitor group voltage outer loop controller; Construct a voltage outer loop PI controller with dead zone for the supercapacitor bank, satisfying the following relationship: Among them, out_i SC (t) is the output signal of the voltage outer loop PI controller with dead zone of the supercapacitor group, K SC_u_p is the control gain of the supercapacitor bank voltage outer loop PI controller, T SC_u_i is the integral time constant of the supercapacitor bank voltage outer loop PI controller; Construct a voltage outer loop PI controller with dead zone for the battery pack, and set the dead zone size to: [-v bat , +v bat ], the dead zone function satisfies the following relationship: Among them, u bat It is the signal input to the battery pack voltage outer loop controller; Construct a voltage outer loop PI controller with dead zone for the battery pack to satisfy the following relationship: Among them, out_i bat (t) is the output signal of the voltage outer loop PI controller with dead zone for the battery pack, K bat_u_p is the control gain of the battery pack voltage outer loop PI controller, T bat_u_i is the integral time constant of the battery pack voltage outer loop PI controller; S42: constructing a supercapacitor bank current inner loop PI controller and a battery bank current inner loop PI controller; Construct the inner loop PI controller of the supercapacitor bank current to satisfy the following relationship: Among them, out_d SC (t) is the output signal of the inner loop PI controller of the supercapacitor group current, e SC (i) is the input signal of the inner loop PI controller of the supercapacitor bank current, K SC_i_p is the control gain of the supercapacitor bank current inner loop PI controller, T SC_i_i is the integral time constant of the inner loop PI controller of the supercapacitor bank current; Construct the battery pack current inner loop PI controller to satisfy the following relationship: Among them, out_d bat (t) is the output signal of the inner loop PI controller of the battery pack current, e bat (i) is the input signal of the battery pack current inner loop PI controller, which is also the current deviation value, K bat_i_p is the control gain of the battery pack current inner loop PI controller, T bat_i_i is the integral time constant of the battery pack current inner loop PI controller.

6. An energy control system for a vehicle-mounted hybrid energy storage system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

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