阅读说明：本技术 一种电动汽车复合电源系统参数匹配方法 (Parameter matching method for composite power supply system of electric automobile ) 是由 刘栋良 杨响攀 崔丽丽 汪建 陈威霖 于 2020-05-21 设计创作，主要内容包括：本发明公开了一种电动汽车复合电源系统参数匹配方法,本发明在电动汽车的复合电源系统参数匹配中,建立了电动汽车的续航里程及超级电容、蓄电池总质量为目标函数,以动力电池单体和超级电容器单体的容量为优化变量的多目标优化模型,并利用加权系数法进行求解。通过以上方法可以计算优化出满足性能指标的动力系统参数,从而减少复合电源系统总质量,增加电动汽车续驶里程。(The invention discloses a parameter matching method for a composite power supply system of an electric automobile, which is characterized in that in the parameter matching of the composite power supply system of the electric automobile, a multi-objective optimization model is established, wherein the endurance mileage, the total mass of a super capacitor and a storage battery of the electric automobile are objective functions, the capacities of a power battery monomer and a super capacitor monomer are taken as optimization variables, and a weighting coefficient method is utilized for solving. The power system parameters meeting the performance indexes can be calculated and optimized through the method, so that the total mass of the composite power supply system is reduced, and the driving range of the electric automobile is increased.)

1. A parameter matching method for a composite power supply system of an electric automobile is characterized by comprising the following steps:

the method comprises the following steps: typical cycle condition hybrid power system demand analysis

Carrying out statistical analysis on the typical cycle working condition to obtain the positive peak power of the typical cycle working condition;

step two: preliminary determination of hybrid power system energy configuration

Aiming at the power battery pack, the driving range of the pure electric vehicle can be met; on the basis, the energy stored by the super capacitor bank can meet the energy value required by continuously providing the peak power-assisted power within a certain time;

step three: determining hybrid power supply system power configuration

The total power provided by the composite power supply system of the pure electric vehicle should meet the maximum positive peak power obtained in the step one;

step four: hybrid power system parameter matching optimization

According to the energy and power configuration of the composite energy storage system, the value ranges of the capacities of the single power battery and the single super capacitor under the conditions that the power battery pack has different parallel branch numbers and the super capacitor pack has different parallel branch numbers are obtained, and are shown in table 1;

with the total mass M of the composite energy storage system_totalAnd mileage S_totalConstructing a multi-objective optimization function by taking the two indexes as optimization targets, and further optimizing key parameters of the composite energy storage system by taking the capacities of the power battery monomer and the super capacitor monomer as optimization variables; wherein the objective function is as shown in formula (1), (2) and formula (3);

J(x)＝αM_total+βS_total(1)

M_total＝N_bats.N_batp.M_bat+N_ucs.N_ucp.M_uc(2)

wherein α is the weighting coefficient of the total mass of the composite power supply storage battery and the super capacitor, β is the weighting coefficient of the endurance mileage, M_batThe mass of the storage battery monomer is taken as the mass of the storage battery monomer; m_ucIs the mass of the super capacitor monomer, N_batsFor the number of monomers in each parallel branch of the composite power supply accumulator, N_batpNumber of parallel branches for accumulator of composite power supply, N_ucsThe number of monomers in each parallel branch of the super capacitor bank is counted; n is a radical of_ucpThe number of the parallel branches of the super capacitor bank is equal to the number of the parallel branches of the super capacitor bank; c_batcellThe capacity value of the power battery monomer is obtained; u shape_batcellIs rated voltage of power battery, v is constant speed, P_reqIs the power required at constant vehicle speed;

and when the alpha and the beta are different coefficients, determining the driving mileage of the electric automobile and the optimal total mass weighting of the super capacitor and the storage battery through a weighting coefficient method.

Technical Field

The invention belongs to the field of composite power supply systems of electric automobiles, and particularly relates to a parameter matching method of a composite power supply system of an electric automobile.

Background

In recent years, with the rapid development of the automobile industry, the global holding amount of automobiles is increasing, and environmental problems and energy problems become hot spots of global concern. The composite power supply system of the electric automobile determines various performance indexes of the automobile during operation, and the operation performance indexes of the automobile can be effectively improved by reasonably matching and optimizing the parameters of the composite power supply system. The traditional matching method of the composite power supply system of the electric automobile needs to meet the requirements of the whole automobile dynamic property of the automobile such as the highest speed, the acceleration time, the maximum climbing gradient and the like. When the storage battery and other energy storage elements in the composite power supply of the electric automobile are used as energy supply sources together, the respective energy and power capacity determine the dynamic property of the whole automobile, the unnecessary cost can be saved by proper matching of the storage battery and the other energy storage elements, the driving range of the electric automobile is increased, and the performance of the whole automobile is optimized.

Disclosure of Invention

The invention provides a parameter matching method for a composite power supply of an electric automobile, aiming at the defects of the parameter matching method for the existing composite power supply system of the electric automobile. The method can reasonably distribute the capacities of the storage battery and the super capacitor, reduce the quality of the composite power supply system of the electric automobile and increase the endurance mileage of the electric automobile.

The invention provides a parameter matching method for a composite power supply system of an electric vehicle, which solves a parameter optimization model of the power supply system on the basis of comprehensively considering the dynamic property and the economical efficiency of the electric vehicle to obtain the optimal parameters of a storage battery and a super capacitor, thereby reducing the quality of the power supply system and increasing the driving range.

The method specifically comprises the following steps:

the method comprises the following steps: typical cycle condition hybrid power system demand analysis

Carrying out statistical analysis on the typical cycle working condition to obtain the positive peak power of the typical cycle working condition; the cycle working condition is the reflection of the actual running state of the vehicle, can provide evaluation and detection standards for the emission or energy consumption of the vehicle, and can provide reference basis for the parameter matching optimization of the vehicle. And respectively carrying out statistical analysis on 3 typical cyclic working conditions of an urban road cyclic working condition (UDDS), a New York CITY cyclic working condition (NYCC) and a Chinese typical urban cyclic working condition (CHINA _ CITY) when the parameters of the composite energy storage system are matched.

Step two: preliminary determination of hybrid power system energy configuration

The composite energy storage system consists of a power battery pack with high specific energy and a super capacitor with high specific power, and can meet the driving range of the pure electric vehicle aiming at the power battery pack; on the basis, the energy stored by the super capacitor bank can meet the energy value required by continuously providing the peak power-assisted power within a certain time;

step three: determining hybrid power supply system power configuration

The total power provided by the composite power supply system of the pure electric vehicle should meet the maximum positive peak power obtained in the step one; according to simulation data, the positive peak power of the UDDS working condition is the largest in the three typical cycle working conditions, so that the maximum power provided by the configurable super capacitor and the storage battery must be larger than the positive peak power of the UDDS.

Step four: hybrid power system parameter matching optimization

According to the energy and power configuration of the composite energy storage system, the value ranges of the capacities of the single power battery and the single super capacitor under the conditions that the power battery pack has different parallel branch numbers and the super capacitor pack has different parallel branch numbers are obtained, and are shown in table 1;

with the total mass M of the composite energy storage system_totalAnd mileage S_totalAnd constructing a multi-objective optimization function by taking the two indexes as optimization targets, and further optimizing the key parameters of the composite energy storage system by taking the capacities of the power battery monomer and the super capacitor monomer as optimization variables. Wherein the objective function is as shown in formula (1), (2) and formula (3).

J(x)＝αM_total+βS_total(1)

M_total＝N_bats.N_batp.M_bat+N_ucs.N_ucp.M_uc(2)

α is a hybrid power supplyThe weighting coefficient of the total mass of the storage battery and the super capacitor, β is the weighting coefficient of the endurance mileage, M_batThe mass of the storage battery monomer is taken as the mass of the storage battery monomer; m_ucIs the mass of the super capacitor monomer, N_batsFor the number of monomers in each parallel branch of the composite power supply accumulator, N_batpNumber of parallel branches for accumulator of composite power supply, N_ucsThe number of monomers in each parallel branch of the super capacitor bank is counted; n is a radical of_ucpThe number of the parallel branches of the super capacitor bank is equal to the number of the parallel branches of the super capacitor bank; c_batcellThe capacity value of the power battery monomer is obtained; u shape_batcellIs rated voltage of power battery, v is constant speed, P_reqIs the power required at constant vehicle speed;

and when the alpha and the beta are different coefficients, determining the driving mileage of the electric automobile and the optimal total mass weighting of the super capacitor and the storage battery through a weighting coefficient method.

Has the advantages that: in the parameter matching of the composite power supply system of the electric automobile, a multi-objective optimization model taking the driving mileage of the electric automobile, the super capacitor and the total mass of the storage battery as objective functions and taking the capacities of the single power battery and the single super capacitor as optimization variables is established, and a weighting coefficient method is utilized for solving. The power system parameters meeting the performance indexes can be calculated and optimized through the method, so that the total mass of the composite power supply system is reduced, and the driving range of the electric automobile is increased.

Drawings

FIG. 1 is a parameter matching diagram of the composite power supply system of the present invention

Detailed Description

The invention is now described in detail with reference to the accompanying drawings, in which:

as shown in the attached figure 1, the invention provides a composite power supply system parameter method for an electric automobile, and particularly provides multi-objective optimization by taking the driving mileage, a super capacitor and the total mass of a storage battery of the electric automobile as objective functions and taking the capacities of a power battery monomer and a super capacitor monomer as optimization variables.

The implementation steps are as follows:

the method comprises the following steps: typical cycle condition hybrid power system demand analysis

In the embodiment, a pure electric vehicle of a certain model of a certain automobile company Limited is taken as a research object. The basic parameters of the whole electric automobile are shown in the table 2:

according to basic parameters of the whole vehicle, parameters such as required power and required energy of the whole vehicle to a composite energy storage system are obtained through simulation on 3 typical cyclic working conditions of an urban road cyclic working condition (UDDS), a New York City cycle worker (NYCC) and a Chinese typical urban cyclic working condition (CHINA _ CITY). Therefore, the maximum positive peak power of the UDDS working condition is obtained, and when the super capacitor and the storage battery are configured, the sum of the maximum powers provided by the super capacitor and the storage battery is required to be larger than the positive peak power of the UDDS.

Step two: preliminary determination of hybrid power system energy configuration

The energy allocation of the power battery pack is determined by the driving range of the pure electric vehicle after one charge. Assuming that the pure electric vehicle runs on a flat and good road surface and the driving range is 300km at a constant speed of 60km/h, the calculation formula (1) shows.

In the formula, S is the total driving range, km; e₃₀₀Energy provided by a power battery when the driving range is 300km, kw.h; p_reqPower required at constant vehicle speed, kw; v is the constant vehicle speed, km/h.

The energy calculation formula (2) of the power battery pack is shown as follows:

E_bat＝C_batcellU_batcellN_batsN_batp(2)

in the formula, E_batThe energy value stored by the power battery pack is W.h; c_batcellThe capacity value of the power battery monomer is A.h; u shape_batcellThe rated voltage of the power battery monomer is 3.2V; n is a radical of_batsFor the number of monomers in each parallel branch of the composite power supply accumulator, N_batpAs a combined power supplyThe number of parallel branches of the storage battery.

The energy value stored by the power battery pack is required to meet the energy required by the endurance mileage of the pure electric vehicle of 300km, and a calculation formula (3) shows that:

E_bat≥1000E₃₀₀(3)

the power battery single cell capacity constraint expression can be obtained by the formulas (2) and (3):

the energy provided by the super capacitor is required to satisfy the following conditions: when the vehicle accelerates from rest to a 50km/h regime within 5 seconds, the peak motor power demand over the entire acceleration can be accommodated.

In the formula, E_ucmaxMaximum energy provided to the supercapacitor, (J); t is t_aThe time taken for stationary acceleration to 50 km/h; p_totalTo drive the peak power of the motor η_mcη for the conversion efficiency of the motor_DC/DCIs the efficiency of the DC/DC converter.

The energy provided by the super capacitor bank is shown by the calculation formula (6):

in the formula, E_ucEnergy provided to the super capacitor; n is a radical of_ucsThe number of monomers in each parallel branch of the super capacitor bank is counted; n is a radical of_ucpThe number of the parallel branches of the super capacitor bank is equal to the number of the parallel branches of the super capacitor bank; c_uccellThe rated capacity of the super capacitor monomer is obtained; u shape_ucmaxThe maximum working voltage of the single super capacitor is obtained; u shape_ucminThe working voltage is half of the cut-off working voltage of the single super capacitor.

The super capacitor monomer capacity constraint expression can be obtained by the formulas (5) and (6):

step three: determining hybrid power supply system power configuration

The total power provided by the composite energy storage system of the electric automobile should meet the maximum positive peak power in three typical cycle working conditions, and it can be known that the positive peak power in the UDDS working condition is the maximum in the three typical cycle working conditions. Obtaining a composite energy storage system power constraint condition formula as shown in a calculation formula (8):

P_bat+P_uc≥P_cymax(8)

P_bat＝P_avg(9)

P_uc＝N_ucsN_ucpm_uccellρ_uc(10)

in the formula, P_cymaxThe maximum positive peak power in three typical cycle conditions, kW; p_avgThe maximum average positive power in the three typical cycle conditions; m is_uccellThe mass of the single super capacitor; rho_ucIs the specific power of the super capacitor.

Step four: hybrid power system parameter matching optimization

According to three constraint equations of the determined composite energy storage system, the equations are formula (4), formula (7) and formula (8)

The value ranges of the capacities of the single power battery and the single super capacitor under the conditions that the power battery pack has different parallel branch numbers and the super capacitor pack has different parallel branch numbers can be obtained, as shown in table 3.

With the total mass M of the composite energy storage system_totalAnd mileage S_totalAnd constructing a multi-objective optimization function by taking the two indexes as optimization targets, and further optimizing the key parameters of the composite energy storage system by taking the capacities of the power battery monomer and the super capacitor monomer as optimization variables. Wherein the objective function is as shown in equations (11), (12) and (13).

J(x)＝αM_total+βS_total(11)

C_total＝N_bats.N_batp.M_bat+N_ucs.N_ucp.M_uc(12)

Wherein α and β are respectively the weighting coefficients of the total mass and the endurance mileage of the composite power supply storage battery and the super capacitor, M_batThe mass of the storage battery monomer is taken as the mass of the storage battery monomer; m_ucThe mass of the super capacitor monomer is shown.

And when the alpha and the beta are different coefficients, determining the driving mileage of the electric automobile and the optimal total mass weighting of the super capacitor and the storage battery through a weighting coefficient method.