阅读说明：本技术 一种增程式电动汽车能量流优化控制方法 (Energy flow optimization control method for extended range electric vehicle ) 是由 孟步敏 张达 申永鹏 刘金刚 傅兵 杨非凡 胡新杰 刘宁杰 于 2021-08-31 设计创作，主要内容包括：本发明公开了一种增程式电动汽车能量流优化控制方法,包括以下步骤：整车能量需求大于内部电池组所能提供能量,确定增程器系统的状态方程；优化目标增程器系统的性能指标,得到增程器系统性能的泛函指标描述；得到离散化后的泛函性能指标和哈密顿函数；求解对应泛函梯度；对增程器内发动机和发电机的扭矩控制矢量进行饱和处理；给定经验值迭代最大值,最终得到使得增程器最优控制变量；将最优控制变量传入增程器内部发动机和发电机,对电动汽车进行控制。本发明将增程器的性能使用具体的函数表示出来进行量化,并通过优化算法进行优化得到最优控制变量并输入到发动机与发电机中得到增程器的最优性能,从而减少整车油耗增加汽车的行驶里程。(The invention discloses an extended range electric vehicle energy flow optimization control method, which comprises the following steps: the energy requirement of the whole vehicle is greater than the energy which can be provided by the internal battery pack, and a state equation of the range extender system is determined; optimizing the performance index of the target range extender system to obtain functional index description of the performance of the range extender system; obtaining a discretized functional performance index and a Hamiltonian; solving the corresponding functional gradient; carrying out saturation treatment on torque control vectors of an engine and a generator in the range extender; giving an iterative maximum value of an empirical value to finally obtain an optimal control variable of the range extender; and transmitting the optimal control variable into an engine and a generator in the range extender to control the electric automobile. The invention uses the concrete function to express the performance of the range extender for quantification, optimizes through an optimization algorithm to obtain the optimal control variable and inputs the optimal control variable into the engine and the generator to obtain the optimal performance of the range extender, thereby reducing the oil consumption of the whole automobile and increasing the driving mileage of the automobile.)

1. An energy flow optimization control method for an extended range electric vehicle is characterized by comprising the following steps:

the method comprises the following steps: judging whether the energy requirement of the whole vehicle is greater than the energy which can be provided by the internal battery pack, if so, entering a second step;

step two: acquiring the required energy of the range extender system, the energy output of the range extender, the energy loss of the range extender, the rotating speed of an engine and the corresponding time, and determining the state equation of the range extender system;

step three: optimizing the performance index of the target range extender system, and further obtaining functional index description of the performance of the range extender system;

step four: carrying out discretization treatment to obtain a discretized functional performance index and constructing a Hamiltonian;

step five: solving the corresponding functional gradient;

step six: carrying out saturation treatment on torque control vectors of an engine and a generator in the range extender to enable the torque and the rotating speed of the engine and the generator to be in an actual range;

step seven: giving an empirical value iteration maximum value, so that convergence is kept to ensure real-time property while iteration is finished within a specified time, and finally obtaining an optimal control variable of the range extender;

step eight: and transmitting the optimal control variable into an engine and a generator in the range extender to control the electric automobile.

2. The energy flow optimization control method for the extended range electric vehicle of claim 1, wherein in the second step, the energy W required by the system of the extended range device is obtained_cmdEnergy output W of range extender_gEnergy loss W of range extender₁Speed omega and corresponding time t_f(ii) a The engine and the ISG motor in the range extender system are coaxially and rigidly connected and have the same rotating speed, wherein the engine transmits an engine torque command T to the electronic control unit through a torque given mode_eTo realize output control, and the corresponding ISG motor controller controls the output of the motor through a motor torque instruction T_gRealizing control;

the corresponding relation exists between the rotating speed, the torque and the efficiency of the engine and the generator,engine efficiency eta_e(ω,T_e) And generator efficiency η_g(ω,T_g) The method is represented by a two-dimensional data table, wherein the range-extending control system is represented by the following state equation:

wherein, J_mAnd B is a viscous friction coefficient.

3. The energy flow optimization control method of the extended range electric vehicle of claim 2, wherein in the third step, the performance of the range extender system is quantified by the following index J:

J＝ε₁(W_g-W_cmd)²+ε₂W₁ ²

the above indicator J is as small as possible to minimize the energy loss while the energy produced by the range extender approaches the given value, where ε₁And ε₂Represents the weight as two constants;

vectorized representation of variables is employed such that x ═ ω W_g W₁]^TAnd u ═ T_e T_g]^TThe state equation of the system is expressed in the form of a constraint equation as follows:

wherein f [ x (t), u (t), t]＝[f₁(·) f₂(·) f₃(·)]^TSpecific variable f₁(·)、f₂(·)、f₃The expression, (. cndot.) is:

x₁refers to a first quantity ω of the vector x，x₂A second quantity W referring to the vector x_g，x₃A third quantity W referring to the vector x₁，u₁A first quantity T referred to as vector u_e,u₂A second quantity T referring to the vector u_g；

Further, the functional index of the system performance of the range extender is described as follows:

4. the energy flow optimization control method of the extended range electric vehicle as claimed in claim 3, wherein in the fourth step, in the control process of the range extender, the controller continuously sends the energy demand command according to the beat of the end time, and in each control period, the initial state is x (t) in each control period₀)＝[ω₀ 0 0]^TWherein, t₀Setting the initial output energy and the loss energy as 0, wherein the initial rotating speed is the final rotating speed at the last moment, and the fuel efficiency optimization control problem of the range extender of the electric automobile is a terminal type optimal control problem of a fixed starting end and a variable terminal;

engine efficiency eta_e(ω,T_e) And generator efficiency η_g(ω,T_g) The method comprises the steps of measuring all characteristic curves for off-line measurement, carrying out discretization processing for realizing control, and using a formulaDiscretization is performed as the following equation:

x(k+1)＝F[x(k),u(k),k]·Δt+x(k)

the continuous time t is discretized into N points, and a parameter k represents a k-th point after discretization; where Δ t is the time occupied by one sampling beat period, and has the following relationship:

k＝0,1,2…,N-1,f[x(t),u(t),t]＝[f_1k(·) f_2k(·) f_3k(·)]^T

the function is specifically expressed as:

the performance index under the discrete system is expressed as a functional as follows:

the following hamiltonian is constructed:

H_k＝λ^T(k+1)F[x(k),u(k),k]

H_kexpressing the Hamiltonian at k, and λ expressing the adjoint of the Hamiltonian;

the adjoint equation is as follows:

wherein the content of the first and second substances, λ (k) represents an accompanying amount at k;

formula (II)The following boundary equations can be obtained:

λ (N) represents a maximum point N after discretization, i.e., an accompanying amount at the final time.

5. The extended range electric vehicle energy flow optimization control method according to claim 4, wherein in the fifth step, the gradient corresponding to the functional J is as follows:

for convenience of calculation, pairThe calculation of (a) is performed as follows:

the following formula is obtained by calculating the linear interpolation:

wherein, ω is_b，ω_sIs x₁(k) The rotating speed of the generator taken in the upper and lower directions, the rotating speed effective data in the efficiency table, and delta omega-omega_b-ω_s，T_bAnd T_sIs u₂(k) Generator rotor with upper and lower directionTorque valid data in torque, efficiency tables, eta_g[ω_s,u₂(k)]The calculation process of (2) is the same as the flow; the following formula is taken for engine efficiency:

the method adopts a linear interpolation method to obtain:

wherein, Δ T ═ T_b-T_s，η_e[x₁(k),T_s]The calculation process of (2) is the same as the above-described flow.

6. The energy flow optimization control method for the extended range electric vehicle as claimed in claim 5, wherein in the sixth step, the torque control vector u ═ T of the engine and the generator due to physical limitation_e T_g]^TCannot be arbitrarily taken in space, which is limited by the maximum and minimum torques of the generator and the engine, which are functions of the speed of rotation, denoted T_emax(omega) and T_gmax(ω), the minimum torque is defined as 0, and the control variables are saturated in the control project as follows:

at the same time, the rotational speed of the range extender is also limited by the maximum and minimum rotational speeds, ω_maxThe smaller of the maximum rotational speeds of the engine and generator, ω_minIs the engine idle speed.

7. The extended range electric vehicle energy flow optimization control method of claim 6, wherein in step seven, in x₁(k)>ω_maxUnder the condition of (1), the torque of the generator at the moment k-1 needs to be increased while the torque of the engine is reduced at the moment k-1, and the rotating speed of the range extender at the moment k needs to be recalculated; and in x₁(k)<ω_minWhen the engine torque is increased at the time k, the generator torque is reduced at the same time, so that the rotating speed of the range extender at the time k is increased; when x is₁(k)>ω_maxThen, the following formula is recalculated:

when x is₁(k)<ω_minThen, the following formula is recalculated:

in the above two formulas, τ is the calculation step of the control variable, and is updated by the following formula:

τ＝(T_emax[x₁(k)]+T_gmax[x₁(k)])/200

the efficiency parameters of the extended range electric vehicle model are combined with a polynomial fitting method to obtain a fitting formula of the maximum torque characteristics of the engine and the generator torque boundary engine, wherein the fitting formula is as follows:

T_emax(ω)＝ρ₄ω⁴+ρ₃ω³+ρ₂ω²+ρ₁ω¹+ρ₀

the maximum torque characteristic of the generator adopts a piecewise fitting method, and the fitting formula is as follows:

where ρ is₀、ρ₁、ρ₂、ρ₃、ρ₄、p₀、p₁、q₁、q₂All the intermediate variables are calculated according to the torque boundary diagram of the engine and the engine in the actual extended range electric automobile.

Technical Field

The invention relates to an energy flow optimization control method for an extended range electric vehicle.

Background

With the rapid development of science and technology, hybrid electric vehicles have become one of the most effective technologies for reducing fuel consumption and increasing the range of the vehicle. The range-extended electric automobile loads the vehicle-mounted charger on the pure electric automobile, so that the vehicle-mounted charger has the advantages of the pure electric automobile, and the defect of insufficient endurance mileage of the pure electric automobile can be overcome, thereby improving the endurance capacity of the electric automobile to a great extent. Therefore, how to improve the performance of the range extender according to the energy requirement of the internal controller of the range-extended electric vehicle to enable the vehicle to have a longer travel is a key issue for improving the energy utilization rate and efficiency of the range-extended electric vehicle.

Disclosure of Invention

In order to solve the technical problems, the invention provides the extended range electric vehicle energy flow optimization control method which is simple in algorithm and high in control precision.

The technical scheme for solving the technical problems is as follows: an energy flow optimization control method for an extended range electric vehicle comprises the following steps:

the method comprises the following steps: judging whether the energy requirement of the whole vehicle is greater than the energy which can be provided by the internal battery pack, if so, entering a second step;

step two: acquiring the required energy of the range extender system, the energy output of the range extender, the energy loss of the range extender, the rotating speed of an engine and the corresponding time, and determining the state equation of the range extender system;

step three: optimizing the performance index of the target range extender system, and further obtaining functional index description of the performance of the range extender system;

step four: carrying out discretization treatment to obtain a discretized functional performance index and constructing a Hamiltonian;

step five: solving the corresponding functional gradient;

step six: carrying out saturation treatment on torque control vectors of an engine and a generator in the range extender to enable the torque and the rotating speed of the engine and the generator to be in an actual range;

step seven: giving an empirical value iteration maximum value, so that convergence is kept to ensure real-time property while iteration is finished within a specified time, and finally obtaining an optimal control variable of the range extender;

step eight: and transmitting the optimal control variable into an engine and a generator in the range extender to control the electric automobile.

In the second step, the energy flow optimization control method for the range-extended electric vehicle obtains the energy W required by the range-extended system_cmdEnergy output W of range extender_gEnergy loss W of range extender₁Speed omega and corresponding time t_f(ii) a The engine and the ISG motor in the range extender system are coaxially and rigidly connected and have the same rotating speed, wherein the engine transmits an engine torque command T to the electronic control unit through a torque given mode_eTo realize output control, and the corresponding ISG motor controller controls the output of the motor through a motor torque instruction T_gRealizing control;

the corresponding relation exists between the rotating speed, the torque and the efficiency of the engine and the generator, and the efficiency eta of the engine_e(ω,T_e) And generator efficiency η_g(ω,T_g) The method is represented by a two-dimensional data table, wherein the range-extending control system is represented by the following state equation:

wherein, J_mFor rotating inertiaAnd B is a viscous friction coefficient.

In the third step, the performance of the range extender system is quantified by the following index J:

J＝ε₁(W_g-W_cmd)²+ε₂W₁ ²

the above indicator J is as small as possible to minimize the energy loss while the energy produced by the range extender approaches the given value, where ε₁And ε₂Represents the weight as two constants;

vectorized representation of variables is employed such that x ═ ω W_g W₁]^TAnd u ═ T_e T_g]^TThe state equation of the system is expressed in the form of a constraint equation as follows:

wherein f [ x (t), u (t), t]＝[f₁(·) f₂(·) f₃(·)]^TSpecific variable f₁(·)、f₂(·)、f₃The expression, (. cndot.) is:

x₁refers to the first quantity ω, x of the vector x₂A second quantity W referring to the vector x_g，x₃A third quantity W referring to the vector x₁，u₁A first quantity T referred to as vector u_e,u₂A second quantity T referring to the vector u_g；

Further, the functional index of the system performance of the range extender is described as follows:

the above-mentioned range-extending powerIn the fourth step, in the control process of the range extender, the controller continuously sends an energy demand instruction according to the beat of the tail end moment, and in each control period, the initial state is x (t)₀)＝[ω₀ 0 0]^TWherein, t₀Setting the initial output energy and the loss energy as 0, wherein the initial rotating speed is the final rotating speed at the last moment, and the fuel efficiency optimization control problem of the range extender of the electric automobile is a terminal type optimal control problem of a fixed starting end and a variable terminal;

engine efficiency eta_e(ω,T_e) And generator efficiency η_g(ω,T_g) The method comprises the steps of measuring all characteristic curves for off-line measurement, carrying out discretization processing for realizing control, and using a formulaDiscretization is performed as the following equation:

x(k+1)＝F[x(k),u(k),k]·Δt+x(k)

the continuous time t is discretized into N points, and a parameter k represents a k-th point after discretization; where Δ t is the time occupied by one sampling beat period, and has the following relationship:

k＝0,1,2…,N-1,f[x(t),u(t),t]＝[f_1k(·) f_2k(·) f_3k(·)]^T

the function is specifically expressed as:

the performance index under the discrete system is expressed as a functional as follows:

the following hamiltonian is constructed:

H_k＝λ^T(k+1)F[x(k),u(k),k]

H_kthe representation is at kλ represents an adjoint quantity of the hamiltonian;

the adjoint equation is as follows:

wherein the content of the first and second substances, λ (k) represents an accompanying amount at k;

formula (II)The following boundary equations can be obtained:

λ (N) represents a maximum point N after discretization, i.e., an accompanying amount at the final time.

In the fifth step, the gradient corresponding to the functional J is:

for convenience of calculation, pairThe calculation of (a) is performed as follows:

the following formula is obtained by calculating the linear interpolation:

wherein, ω is_b，ω_sIs x₁(k) The rotating speed of the generator taken in the upper and lower directions, the rotating speed effective data in the efficiency table, and delta omega-omega_b-ω_s，T_bAnd T_sIs u₂(k) Torque effective data in the efficiency table, eta, of the generator taken in two directions_g[ω_s,u₂(k)]The calculation process of (2) is the same as the flow; the following formula is taken for engine efficiency:

the method adopts a linear interpolation method to obtain:

wherein, Δ T ═ T_b-T_s，η_e[x₁(k),T_s]The calculation process of (2) is the same as the above-described flow.

In the sixth step of the energy flow optimization control method for the extended range electric vehicle, the torque control vector u of the engine and the generator is [ T ═ T ] due to physical limitation_e T_g]^TCannot be arbitrarily classified in spaceValue limited by the maximum and minimum torques of the generator and engine as a function of the speed, denoted T_emax(omega) and T_gmax(ω), the minimum torque is defined as 0, and the control variables are saturated in the control project as follows:

at the same time, the rotational speed of the range extender is also limited by the maximum and minimum rotational speeds, ω_maxThe smaller of the maximum rotational speeds of the engine and generator, ω_minIs the engine idle speed.

In the seventh step, in x, the energy flow optimization control method for the extended range electric vehicle₁(k)>ω_maxUnder the condition of (1), the torque of the generator at the moment k-1 needs to be increased while the torque of the engine is reduced at the moment k-1, and the rotating speed of the range extender at the moment k needs to be recalculated; and in x₁(k)<ω_minWhen the engine torque is increased at the time k, the generator torque is reduced at the same time, so that the rotating speed of the range extender at the time k is increased; when x is₁(k)>ω_maxThen, the following formula is recalculated:

when x is₁(k)<ω_minThen, the following formula is recalculated:

in the above two formulas, τ is the calculation step of the control variable, and is updated by the following formula:

τ＝(T_emax[x₁(k)]+T_gmax[x₁(k)])/200

the efficiency parameters of the extended range electric vehicle model are combined with a polynomial fitting method to obtain a fitting formula of the maximum torque characteristics of the engine and the generator torque boundary engine, wherein the fitting formula is as follows:

T_emax(ω)＝ρ₄ω⁴+ρ₃ω³+ρ₂ω²+ρ₁ω¹+ρ₀

the maximum torque characteristic of the generator adopts a piecewise fitting method, and the fitting formula is as follows:

where ρ is₀、ρ₁、ρ₂、ρ₃、ρ₄、p₀、p₁、q₁、q₂All the intermediate variables are calculated according to the torque boundary diagram of the engine and the engine in the actual extended range electric automobile.

The invention has the beneficial effects that: the invention uses a specific function to express the performance of the range extender for quantification, optimizes the performance by a multi-objective optimization algorithm to obtain the torque of the optimal control variable engine and the generator, and finally inputs the optimal control variable into the engine and the generator by the range-extending optimization controller to obtain the optimal performance of the range extender, thereby reducing the oil consumption of the whole vehicle and increasing the driving mileage of the vehicle.

Drawings

FIG. 1 is a flow chart of the present invention.

Fig. 2 is a schematic diagram of the working principle of the range-extending controller.

FIG. 3 is a flow chart of global optimization.

Detailed Description

The invention is further described below with reference to the figures and examples.

As shown in fig. 1, an energy flow optimization control method for an extended range electric vehicle includes the following steps:

the method comprises the following steps: and judging whether the energy requirement of the whole vehicle is greater than the energy which can be provided by the internal battery pack, if so, entering a step two.

Step two: and acquiring the required energy of the range extender system, the energy output of the range extender, the energy loss of the range extender, the rotating speed of the engine and the corresponding time, and determining the state equation of the range extender system.

Obtaining the required energy W of the range extender system_cmdEnergy output W of range extender_gEnergy loss W of range extender₁Engine speed omega and corresponding time t_f。

The working principle of the range-extending type optimization controller is shown in figure 2, an engine and an ISG motor in the range-extending device system are coaxially and rigidly connected, wherein the engine sends an engine torque command T to an electronic control unit through a torque given mode_eTo realize output control, and the corresponding ISG motor controller controls the output of the motor through a motor torque instruction T_gRealizing control;

the corresponding relation exists between the rotating speed, the torque and the efficiency of the engine and the generator, and the efficiency eta of the engine_e(ω,T_e) And generator efficiency η_g(ω,T_g) The method is represented by a two-dimensional data table, wherein the range-extending control system is represented by the following state equation:

wherein, J_mAnd B is a viscous friction coefficient.

Step three: and optimizing the performance index of the target range extender system, and further obtaining functional index description of the performance of the range extender system.

The performance of the range extender system is quantified with the following indicator J:

J＝ε₁(W_g-W_cmd)²+ε₂W₁ ²

the above indicator J being as small as possible to enable the energy produced by the range extender to approach a given valueAt the same time, the energy loss is as small as possible, wherein₁And ε₂Represents the weight as two constants;

vectorized representation of variables is employed such that x ═ ω W_g W₁]^TAnd u ═ T_e T_g]^TThe state equation of the system is expressed in the form of a constraint equation as follows:

wherein f [ x (t), u (t), t]＝[f₁(·) f₂(·) f₃(·)]^TSpecific variable f₁(·)、f₂(·)、f₃The expression, (. cndot.) is:

x₁refers to the first quantity ω, x of the vector x₂A second quantity W referring to the vector x_g，x₃A third quantity W referring to the vector x₁，u₁A first quantity T referred to as vector u_e,u₂A second quantity T referring to the vector u_g；

Further, the functional index of the system performance of the range extender is described as follows:

step four: and carrying out discretization treatment to obtain a discretized functional performance index and constructing a Hamiltonian.

In the control process of the range extender, the controller continuously sends an energy demand instruction according to the beat of the tail end time, and the initial state is x (t) in each control period₀)＝[ω₀00]^TWherein, t₀Setting the initial output energy and the loss energy as 0 as the initial rotation speed, namely the final rotation speed at the last momentThe optimal control problem of the fuel efficiency of the vehicle range extender is a terminal type optimal control problem of a fixed starting end and a variable terminal;

engine efficiency eta_e(ω,T_e) And generator efficiency η_g(ω,T_g) The method comprises the steps of measuring all characteristic curves for off-line measurement, carrying out discretization processing for realizing control, and using a formulaDiscretization is performed as the following equation:

x(k+1)＝F[x(k),u(k),k]·Δt+x(k)

the continuous time t is discretized into N points, and a parameter k represents a k-th point after discretization; where Δ t is the time occupied by one sampling beat period, and has the following relationship:

k＝0,1,2…,N-1,f[x(t),u(t),t]＝[f₁(·) f₂(·) f₃(·)]^T

the function is specifically expressed as:

the performance index under the discrete system is expressed as a functional as follows:

the following hamiltonian is constructed:

H_k＝λ^T(k+1)F[x(k),u(k),k]

H_kexpressing the Hamiltonian at k, and λ expressing the adjoint of the Hamiltonian;

the adjoint equation is as follows:

wherein the content of the first and second substances, λ (k) represents an accompanying amount at k;

formula (II)The following boundary equations can be obtained:

λ (N) represents a maximum point N after discretization, i.e., an accompanying amount at the final time.

Step five: the corresponding functional gradient is solved.

The gradient corresponding to functional J is:

for convenience of calculation, pairThe calculation of (a) is performed as follows:

the following formula is obtained by calculating the linear interpolation:

wherein, ω is_b，ω_sIs x₁(k) The rotating speed of the generator taken in the upper and lower directions, the rotating speed effective data in the efficiency table, and delta omega-omega_b-ω_s，T_bAnd T_sIs u₂(k) Torque effective data in the efficiency table, eta, of the generator taken in two directions_g[ω_s,u₂(k)]The calculation process of (2) is the same as the flow; the following formula is taken for engine efficiency:

the method adopts a linear interpolation method to obtain:

wherein, Δ T ═ T_b-T_s，η_e[x₁(k),T_s]The calculation process of (2) is the same as the above-described flow.

Step six: and carrying out saturation treatment on the torque control vectors of the engine and the generator in the range extender so that the torque and the rotating speed of the engine and the generator are in a practical range.

Due to physical limitations, the torque control vector u of the engine and the generator is ═ T_e T_g]^TCannot be arbitrarily taken in space, which is limited by the maximum and minimum torques of the generator and the engine, which are functions of the speed of rotation, denoted T_emax(omega) and T_gmax(ω), the minimum torque is defined as 0, and the control variables are saturated in the control project as follows:

at the same time, the rotational speed of the range extender is also limited by the maximum and minimum rotational speeds, ω_maxThe smaller of the maximum rotational speeds of the engine and generator, ω_minIs the engine idle speed.

Step seven: and giving an empirical value iteration maximum value, so that convergence is kept to ensure real-time property while iteration is finished in a specified time, and finally, the optimal control variable of the range extender is obtained.

At x₁(k)>ω_maxUnder the condition of (1), the torque of the generator at the moment k-1 needs to be increased while the torque of the engine is reduced at the moment k-1, and the rotating speed of the range extender at the moment k needs to be recalculated; and in x₁(k)<ω_minWhen the engine torque is increased at the time k, the generator torque is reduced at the same time, so that the rotating speed of the range extender at the time k is increased; when x is₁(k)>ω_maxThen, the following formula is recalculated:

when x is₁(k)<ω_minThen, the following formula is recalculated:

in the above two formulas, τ is the calculation step of the control variable, and is updated by the following formula:

τ＝(T_emax[x₁(k)]+T_gmax[x₁(k)])/200

the efficiency parameters of the extended range electric vehicle model are combined with a polynomial fitting method to obtain a fitting formula of the maximum torque characteristics of the engine and the generator torque boundary engine, wherein the fitting formula is as follows:

T_emax(ω)＝ρ₄ω⁴+ρ₃ω³+ρ₂ω²+ρ₁ω¹+ρ₀

the maximum torque characteristic of the generator adopts a piecewise fitting method, and the fitting formula is as follows:

where ρ is₀、ρ₁、ρ₂、ρ₃、ρ₄、p₀、p₁、q₁、q₂All intermediate variables are calculated according to torque boundary diagrams of an engine and an engine in an actual extended range electric automobile, a specific flow chart of global optimization is shown in figure 3, i_maxThe method is determined by empirical values, and can ensure convergence while finishing iteration within a specific time in most cases, so as to ensure the instantaneity of the range extender fuel efficiency optimization control system.

Step eight: and transmitting the optimal control variable into an engine and a generator in the range extender to control the electric automobile.

The invention uses a specific function to express the performance of the range extender for quantification, optimizes the performance by a multi-objective optimization algorithm to obtain the torque of the optimal control variable engine and the generator, and finally inputs the optimal control variable into the engine and the generator by the range-extending optimization controller to obtain the optimal performance of the range extender, thereby reducing the oil consumption of the whole vehicle and increasing the driving mileage of the vehicle. Iterative maximum i among algorithms_maxThe method is determined by empirical values, and can ensure convergence while finishing iteration within a specific time in most cases, so as to ensure the instantaneity of the range extender fuel efficiency optimization control system.