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

Abstract

The invention relates to the technical field of urban rail transit energy storage, and discloses an energy control method and system for a vehicle-mounted hybrid energy storage system. According to the method, by calculating the output power of a train traction motor, the relation between the charge state of a super capacitor set and terminal voltage and the relation between the charge state of a storage battery set and current are established; a fuzzy quantizer, a fuzzy inference device and a fuzzy rule updater of a super capacitor group and a storage battery group are constructed, a voltage outer loop PI controller with a dead zone and a current inner loop PI controller with a dead zone are constructed for the super capacitor group and the storage battery group, and a control signal of a bidirectional DC / DC converter is obtained, so that the stability of the DC bus voltage is maintained, and the energy-saving rate is improved.

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 a vehicle-mounted hybrid energy storage system. Background Art

[0002] In the field of urban rail transit, with the acceleration of urbanization and the increase in traffic demand, the demand for efficient, reliable and energy-saving electric traction systems is growing. As a key technology to improve the energy efficiency of rail transit vehicles, the on-board hybrid energy storage system effectively supports the stable operation of the system and the optimal use of energy through intelligent management of energy flow.

[0003] In the existing technology, the energy control methods of vehicle-mounted hybrid energy storage systems mostly adopt rule-based control strategies, which often lack in-depth understanding and prediction capabilities of the system's dynamic characteristics. In addition, due to the complex and changeable operating environment and other reasons, the existing technology still has shortcomings in maintaining the stability of the DC bus voltage and improving the energy saving rate, and the system's energy saving potential has not been fully utilized. 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 by 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: Acquire parameter information of a target train traction motor, and calculate the output power of the train traction motor 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 the 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, wherein the processor implements the steps of the method described in the first aspect when executing the computer program.

[0013] Beneficial effects:

[0014] The present application provides an energy control method for a vehicle-mounted 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, which is applicable to the variable working conditions of complex actual systems; the energy control strategy is generated by using fuzzy rules to improve 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 process of the energy storage unit is optimized, energy loss is reduced, and the energy utilization efficiency of the system is improved. The DC bus voltage is maintained stable, and the impact of voltage fluctuations on the electric traction system is reduced, 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 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 It is a topological schematic 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 It is an overall structural block diagram 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 It is a 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 5It 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 It 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 : is a DC bus voltage comparison diagram of an energy control method for a vehicle-mounted hybrid energy storage system according to a preferred embodiment of the present invention;

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

[0024] The technical solution of the present invention is described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] Unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the usual meanings understood by persons with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words 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 "one" do not indicate quantity restrictions, but indicate the existence of at least one. Words such as "connect" 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 also Figure 1 , the present application provides an energy control method for a vehicle-mounted hybrid energy storage system, comprising:

[0027] S1: Acquire parameter information of a target train traction motor, and calculate the output power of the train traction motor 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 noting that to implement energy control on the hybrid energy storage system, it is necessary to know the current energy level in each energy storage group, but the energy level is usually not measurable by suitable sensors. The state of charge (SOC) describes the ratio of the current remaining capacity of the battery to its fully charged state capacity during battery use, and is usually used to reflect the current energy level in the energy storage group. For supercapacitor groups, the relationship between the state of charge of the supercapacitor group and the terminal voltage is established, and the current state of charge can be obtained through the measurable terminal voltage; for battery groups, their characteristics are complex, and the relationship between the state of charge of the battery group and the current needs to be established based on the state of charge mechanism. Through the measurable current, the current integration is used to obtain the state of charge up to the current period.

[0030] 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;

[0031] S4: setting the 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;

[0032] 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.

[0033] The above-mentioned energy control method for a vehicle-mounted hybrid energy storage system can realize the effective utilization of energy in the hybrid energy storage system. This method can be applied to the variable operating conditions of complex actual systems. According to different vehicle energy requirements, different operating conditions and operating loads, the energy in the energy storage system can be effectively utilized. This method uses fuzzy rules to generate energy control strategies, which improves the robustness of the system; and improves the dynamic performance of the system by updating the fuzzy rules. By controlling the energy 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. Maintain the stability of the DC bus voltage and reduce the impact of voltage fluctuations on the electric traction system, thereby enhancing the stability and reliability of the entire system.

[0034] The steps of the above method are described in detail below with a complete embodiment.

[0035] 1. Please see 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 to satisfy 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 and terminal voltage of the supercapacitor group, and the state of charge and current of the battery group respectively.

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

[0041]

[0042] Among them, SOC SC is the charge state 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 supercapacitor bank fuzzy quantizer.

[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 output of the supercapacitor group fuzzy quantizer corresponds 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, 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 (such as Gaussian function), S-shaped, Z-shaped, trapezoidal and other forms. The specific one depends on which membership function the system works better under, and is usually selected by experimental method. In the embodiment of this patent, triangular and linear membership functions are selected as continuous functions.

[0052] Step 2: Construct the 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 respectively 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, respectively, 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 the supercapacitor group fuzzy reasoner.

[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 device is the supercapacitor bank charge and discharge threshold value U th_SC ;

[0058] Step 4: Construct the 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. 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 charging and discharging thresholds of the supercapacitor group and the battery group for the The membership degree of the ρ fuzzy centers satisfies the following relationship:

[0061]

[0062] in, They are respectively the charge and discharge thresholds of the supercapacitor group and the battery group. The membership degree of the 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 charge state SOC, traction motor output power P out domain, 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, μ SC (SOC SC ))、 μ bat (SOC SC)) respectively represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on U×S, They 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 group and the battery group on U×P respectively. Among them, the "×" symbol is a special operator, which represents the fuzzy product operation in the composite fuzzy relation operation and is one of the composite fuzzy relation set synthesis operations.

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

[0064]

[0065] In the formula, Indicates that in all membership In the value selection, return the value with the largest calculated value in [·]; 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 to defuzzify and 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] Supercapacitor and battery pack charge and discharge threshold fuzzy set ρ fuzzy centers satisfy the following relationship:

[0071]

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

[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 reasoner and the DC bus voltage, and the output is the rule reorganization update level. In the early stage of the train start-up process, the DC bus voltage will decrease 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. At this time, lowering the discharge threshold can achieve this purpose. In the later stage of the train start-up, the train is about to enter a uniform speed driving 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 purpose; when the train brakes, Δu and Δu′ will increase but the sign is opposite to that when the train starts. At this time, the energy storage device needs to quickly enter the charging state and absorb energy. At this time, lowering the charging threshold can achieve this purpose. 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 is updated.

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

[0077]

[0078] Among them, ω′ represents the division level of the supercapacitor group charge and discharge threshold after the fuzzy rule is updated, ω′=1,2,…,Ω′, ω represents the division level of the current supercapacitor group charge and discharge threshold, ω=1,2,…,Ω, Δu is the charge and discharge threshold U output by the fuzzy reasoner of the battery group th_bat The deviation between the DC bus voltage and 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 about 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,L,P SC ,q SC=1,2,3,L,Q SC , and p SC >q SC , a SC ,b SC ,c SC is a constant.

[0081] The input of the battery pack fuzzy rule updater is the charge and discharge threshold U output by the battery pack fuzzy reasoner. th_bat The deviation Δu between the DC bus voltage, the deviation change rate Δu′ and the current battery pack charge and discharge threshold division level ξ; the fuzzy rule updater outputs the battery pack charge and discharge threshold division level after the fuzzy rule is updated.

[0082] After the fuzzy rules are updated, the battery pack charge and discharge thresholds are divided into levels, satisfying the following relationship:

[0083]

[0084] 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 about Δu and Δu′, which satisfies the following relationship:

[0085]

[0086] Among them, p bat ,q bat Indicates the value of increasing or decreasing the charge and discharge threshold division level of the battery pack, p bat =1,2,3,L,P bat ,q bat =1,2,3,L,Q bat , and p bat >q bat , a bat ,b bat ,c bat is a constant.

[0087] 4. Please see Figure 3 , respectively construct the voltage outer loop PI controller and current inner loop PI controller with dead zone for the supercapacitor group and the battery group, specifically:

[0088] 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:

[0089]

[0090] Among them, u SC 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 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 The signal for inputting the battery pack voltage outer loop controller;

[0097] The voltage outer loop PI controller of the battery pack 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 inner loop PI controller of the supercapacitor bank current, which is also the current deviation value, K SC_i_p is the control gain of the inner loop PI controller of the supercapacitor bank current, 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 inner loop PI controller of the battery pack current, which is also the current deviation value, K bat_i_p is the control gain of the inner loop PI controller of the battery pack current, T bat_i_i is the integral time constant of the inner loop PI controller of the battery pack current.

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

[0107] The urban rail transit system in the above embodiment is a power supply system with a DC bus voltage of 1500V, a maximum vehicle speed of 120Km / h, and an allowable fluctuation range of the DC bus voltage of 1000V-1800V. Figure 4 The membership function of the supercapacitor group and the battery group is shown in 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 in the figure, the traction network power required by the train is 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 embodiment of the present application also provides an on-board hybrid energy storage system energy control system, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program. The on-board hybrid energy storage system energy control system can implement various embodiments of the above method and achieve the same beneficial effects, which will not be described in detail here.

[0122] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A method for controlling energy of a vehicle-mounted hybrid energy storage system, characterized in that: include: S1: Acquire parameter information of a 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 the 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-mounted hybrid energy storage system.

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 the angular velocity of the traction motor; S1 includes: S11: Calculate the output power of the train traction motor to satisfy 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, satisfying the following relationship: Among them, SOC SC is the charge state of the supercapacitor bank, U SC_t is the current terminal voltage of the supercapacitor bank, U SC_N is the rated terminal voltage of the supercapacitor bank; S22: Establish the relationship between the state of charge of the battery pack and the 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 S3 includes: S31: constructing a fuzzy quantizer for the supercapacitor group and a fuzzy quantizer for the battery group respectively; 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, to divide ε, δ, and γ fuzzy centers, and the outputs of the supercapacitor group fuzzy quantizer correspond 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, 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, respectively, 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; S32: constructing a fuzzy reasoning machine for the supercapacitor group and a fuzzy reasoning machine for the battery group respectively; 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 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. 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 maximum and minimum reasoning, the membership of the charge and discharge thresholds of the supercapacitor group and the battery group to the θth and ρth fuzzy centers are solved respectively, satisfying the following relationship: in, are the membership of the charge and discharge thresholds of the supercapacitor group and the battery group to the θth and ρth fuzzy centers, θ=1,2,…,Γ, ρ=1,2,…,γ, ∨ means taking the maximum, ∧ means taking the minimum, U, S, P are the DC bus voltage U dc , energy storage device charge state SOC, traction motor output power P out domain, 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, They represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on U×S, They represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on S×P, They represent the composite fuzzy relationship membership of the supercapacitor group and the battery group on U×P respectively; The composite fuzzy relation membership satisfies the following relationship: In the formula, It means that among all the values ​​of membership θ, the value with the largest calculated value 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 to defuzzify and 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 are the charge and discharge thresholds of the supercapacitor group and the battery group, u θ_SC 、u ρ_bat are the θth and ρth fuzzy centers of the fuzzy sets of charge and discharge thresholds of the supercapacitor group and the battery group, respectively, θ=1,2,…,Γ, ρ=1,2,…,γ; The θth and ρth fuzzy centers of the supercapacitor and battery charge and discharge threshold fuzzy sets satisfy the following relationship: Among them, U dc_max , U dc_min They respectively represent the maximum and minimum values ​​of the allowable fluctuation of the DC bus voltage; S33: constructing a fuzzy rule updater for the supercapacitor group and a fuzzy rule updater for the battery group respectively; 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 is updated; After the fuzzy rules are updated, the supercapacitor bank charge and discharge thresholds are divided into levels, satisfying the following relationship: Among them, ω′ represents the division level of the supercapacitor group charge and discharge threshold after the fuzzy rule is updated, ω′=1,2,…,Ω′, ω represents the division level of the current supercapacitor group charge and discharge threshold, ω=1,2,…,Ω, Δu is the charge and discharge threshold U output by the fuzzy reasoner of the battery group th_bat The deviation between the DC bus voltage and 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 about 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,L,P SC ,q SC =1,2,3,L,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 U output by the battery pack fuzzy reasoner. th_bat The fuzzy rule updater outputs the battery group charge and discharge threshold division level after the fuzzy rule is updated; the deviation Δu between the DC bus voltage, the deviation change rate Δu′ and the current battery group charge and discharge threshold division level ξ; After the fuzzy rules are updated, the battery pack charge and discharge thresholds are divided into levels, satisfying the following relationship: Wherein, 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 about 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 division level of the battery pack, p bat =1,2,3,L,P bat ,q bat =1,2,3,L,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: constructing a voltage outer loop PI controller for the supercapacitor group and a voltage outer loop PI controller with a 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 The signal input to the supercapacitor group voltage outer loop controller; Construct a voltage outer loop PI controller with a dead zone for the supercapacitor group to satisfy 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 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 The signal for inputting 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 group current inner loop PI controller and a battery group 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 inner loop PI controller of the supercapacitor bank current, 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 inner loop PI controller of the battery pack current, which is also the current deviation value, K bat_i_p is the control gain of the inner loop PI controller of the battery pack current, T bat_i_i is the integral time constant of the inner loop PI controller of the battery pack current.

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 described in any one of claims 1 to 5 are implemented.

Images