CN110530048B - Transcritical CO2Air-conditioning heat pump system and optimization control method thereof - Google Patents

Abstract

The invention discloses a transcritical CO₂An air-conditioning heat pump system and an optimization control method thereof, which firstly provide a control method combining a multi-parameter extremum search control algorithm and a self-learning neural network aiming at how to quickly and accurately adaptively adjust the performance of an air-conditioning system under different automobile driving environment working conditions, and carry out high-pressure (P) operation on four optimized parameters of the air-conditioning system, namely the system_h) Air volume (V) of external heat exchanger_gasc) Evaporation temperature (T)_e) And effective superheat (T)_sup) The optimization is carried out, and then a specific control strategy of four optimized parameters is further proposed. The air conditioner of the new energy automobile can be rapidly self-regulated all the time under various changeable and complex driving environment working conditions, the comfort requirement of passengers on a carriage is met under the lowest energy consumption in the shortest time, and the future energy crisis is relieved.

Description

Transcritical CO2Air-conditioning heat pump system and optimization control method thereof

Technical Field

The invention belongs to the field of transcritical carbon dioxide systems, and particularly relates to a transcritical CO2 air conditioning system of a new energy automobile and an optimization control method thereof.

Background

The new energy automobile overcomes the problem of fossil fuel dependence of fuel oil automobiles, is diversified in energy utilization, quiet and environment-friendly, and represents the development trend of future automobiles. The new energy automobile is different from a fuel automobile, no engine waste heat can be used for heating air in a compartment at low ambient temperature, so that the pure new energy automobile basically adopts PTC electric heating to heat in winter at present, however, the vehicle-mounted battery of the pure new energy automobile has limited electric storage capacity, and the electric heating is adopted to influence the driving range of the automobile. The heating coefficient of the heat pump type air conditioning system is more than 1, and compared with electric heating, the heat pump type air conditioning system has the characteristics of high efficiency and energy saving and is more beneficial to the development of pure and new energy automobiles. The most widely used refrigerant of the traditional automobile air conditioning system is R134a, the environmental protection performance is poor, the refrigerant is gradually eliminated, the automobile is in the driving process, the environment is changeable, the driving speed needs to be reduced according to requirements according to road regulations when the automobile runs in severe traffic jam conditions, rainy and snowy weather, heavy fog and other weather, the air quantity of a gas cooler is reduced, the requirement on the heating performance of the automobile air conditioner is higher, and therefore the refrigerant is also a great test for the traditional working medium and is difficult to meet the actual requirement. And CO₂The refrigerant has obvious advantages as a natural refrigerant. Transcritical CO₂The heat pump cycle has unique advantages, the temperature of the heat release process is high, and a considerable temperature slip (about 80-100 ℃) exists. The research shows that: when the evaporation temperature is 0 ℃, the water temperature can be heated from 0 ℃ to 60 ℃, the COP of the heat pump can reach 4.3, and the energy consumption is reduced by 75 percent compared with that of an electric water heater and a gas water heater. In cold regions, the heating capacity and efficiency of the conventional air source heat pump decrease rapidly with the decrease of ambient temperature, and the use of the heat pump is limited. And CO₂The heat pump system can maintain higher heat supply amount and higher water outlet temperature in a low-temperature environment, and energy consumed by the auxiliary heating equipment is greatly saved.

The circulation of the transcritical carbon dioxide circulation in the supercritical state is characterized in that the COP of the system can be controlled to reach the maximum value by controlling the pressure of the high-pressure side, and a method for further controlling the pressure value of the high-pressure side to reach a larger value can be adopted if necessary, so that higher refrigerating capacity is obtained at the cost of higher energy consumption. The system works under the strong refrigerating capacity, the refrigerating capacity is large, the temperature in the carriage is reduced more rapidly, but the corresponding power consumption is also larger, therefore, when the automobile starts to run and runs stably, the reasonable control of the working state of the automobile air conditioner is necessary, the comfort requirement of passengers can be met in the shortest possible time, the energy consumption is reduced, and the energy is saved.

The existing transcritical carbon dioxide automobile air conditioning system lacks an effective control logic in a control mode and a corresponding high-efficiency and high-precision control system, so that the air conditioning system cannot be operated in a state corresponding to the optimal performance under different environmental working conditions, and the aim of optimal real-time operation is fulfilled.

Disclosure of Invention

The invention aims to provide a new energy automobile trans-critical CO₂The air conditioning system and the optimization control method thereof enable the air conditioning system to operate in a state corresponding to the optimal performance of the air conditioning system under different environmental working conditions, so as to solve the technical problems.

In order to realize the purpose, the following technical scheme is adopted:

new energy automobile trans-critical CO₂An air conditioning system comprising: the system comprises a compressor, a four-way reversing valve, an in-vehicle heat exchanger, a heat regenerator, an electronic expansion valve, an out-vehicle heat exchanger, a three-way valve and a liquid storage device;

the outlet of the compressor is connected with a port d of the four-way reversing valve, a port a of the four-way reversing valve is connected with one end of the heat exchanger outside the vehicle, a port c of the four-way reversing valve is sequentially connected with the heat exchanger inside the vehicle, the electronic expansion valve and the first heat exchange pipeline of the heat regenerator and the other end of the heat exchanger outside the vehicle, a port b of the four-way reversing valve is connected with a port c of the three-way valve, the port a of the three-way valve is connected with the inlet of the liquid accumulator through the second heat exchange pipeline of the heat regenerator, the port b of the three-way valve and the second heat exchange pipeline.

Further, the optimization is performed by adopting a multivariate extreme value search control method, which comprises the following steps:

four target parameters: coefficient of performance COP value and refrigerating capacity Q of air conditioning system_cHeating capacity Q_hAnd the air-conditioner air-out temperature T_out；

Four optimization parameters: operating high pressure value P of air conditioning system_hAir volume V of external heat exchanger_gascEvaporation temperature T_eAnd effective superheat T_sup；

The four target parameters are target quantities of the multivariable extremum search control method, and the four optimized parameters are control quantities of the multivariable extremum search control method;

in the cooling mode in summer: the target quantities of the multivariable extremum search control method are respectively the performance coefficient COP value and the refrigerating capacity Q of the air conditioning system_cAnd the air outlet temperature T of the air conditioner_outThe control quantity is the running high-pressure value P of the system_hAir volume V of external heat exchanger_gascEvaporation temperature T_eAnd effective superheat T_sup(ii) a Refrigerating capacity Q of air conditioning system_cAnd the air-conditioner air-out temperature T_outAre respectively Q_c0And T_out0The multivariable extremum searching control method searches for the optimal values of the four control variables when the performance parameter COP of the system reaches the maximum value on the premise that the refrigerating capacity is not lower than a set value; and controlling the new energy automobile trans-critical CO by an optimal value₂Operating an air conditioning system;

in the winter heating mode: the target quantities of the multivariable extreme value search control method are respectively the performance coefficient COP value and the heating capacity Q of the air conditioning system_hAnd the air-conditioner air-out temperature T_outThe control quantity is the running high-pressure value P of the system_hAir volume V of external heat exchanger_gascEvaporation temperature T_eAnd effective superheat T_sup(ii) a Heating capacity Q of air conditioning system_hAnd the air-conditioner air-out temperature T_outAre respectively Q_h0And T_out0The multivariable extreme value search control system finds the optimal values of the four control variables when the performance parameter COP of the system reaches the maximum value on the premise that the heating capacity and the air outlet temperature are not lower than set values; and controlling the new energy automobile trans-critical CO by an optimal value₂The air conditioning system operates.

Further, in the variable searching process, the extreme values of a plurality of variables are simultaneously optimized so as to find the input problem of the air conditioning system with the best performance under any condition:

(P_h-opt(t),V_gasc-opt(t),T_e-opt(t)，T_sup-opt(t))＝argminf(P_h，P_l,V_gasc,T_e,T_sup,t)

wherein: p_h，V_gasc,T_e，T_supAre respectively input control variablesAn amount;

P_h-opt(t),V_gasc-opt(t),T_e-opt(t),T_sup-opt(t) output merit values, respectively;

f(P_h，V_gasc,T_e,T_supand t) is a non-linear system performance function for static or slow time-varying.

Further, in a cooling mode in summer: high pressure P for optimum operation of output using multivariate extreme search control method_h-optOptimal air volume V of external heat exchanger_gasc-optOptimum evaporation temperature T_e-optAnd an optimum effective superheat T_sup-optRespectively obtaining the refrigerating capacity Q of the air conditioning system as an initial value_cAnd the air-conditioner air-out temperature T_out；

If the refrigerating capacity and the outlet air temperature do not satisfy Q_c≥Q_c0、T_out≤T_out0Then by Δ P_h＝0.1MPa，△V_gasc＝10m³/h、△ T_e＝0.2℃、△T_supGradient of 0.2 deg.C, and taking ith order value of four optimized parameters, i.e. P_h-opt-i、V_gasc-opt-i、T_e-opt-i、 T_sup-opt-iAnd P_h-opt+i、V_gasc-opt+i、T_e-opt+i、T_sup-opt+i；

The value is determined by the following formula:

P_h-opt-i＝P_h-opt-i·ΔP_h

V_gasc-opt-i＝V_gasc-opt-i·ΔV_gasc

T_e-opt-i＝T_e-opt-i·ΔT_e

T_sup-opt-i＝T_sup-opt-i·ΔT_sup

P_h-opt+i＝P_h-opt+i·ΔP_h

V_gasc-opt+i＝V_gasc-opt+i·ΔV_gasc

T_e-opt+i＝T_e-opt+i·ΔT_e

T_sup-opt+i＝T_sup-opt+i·ΔT_sup

wherein i is 1,2,3

Step one, when i is equal to 1, four optimization parameters respectively have 3 values: p_h-opt、P_h-opt-1、P_h-opt+1、V_gasc-opt、V_gasc-opt-1、 V_gasc-opt+1、T_e-opt、T_e-opt-1、T_e-opt+1、T_sup-opt、T_sup-opt-1、T_sup-opt+1Randomly dereferencing each optimized parameter, and performing permutation and combination to obtain 3 in total⁴Respectively acquiring trans-critical CO of the new energy automobile under each condition₂Refrigerating capacity Q of air conditioning system_cAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step two, if the results obtained in the step one do not satisfy Q_c≥Q_c0、T_out≤T_out0If i is equal to 2, then the four optimization parameters are increased by two values, i.e. P_h-opt-2、P_h-opt+2、V_gasc-opt-2、V_gasc-opt+2、T_e-opt-2、T_e-opt+2、T_sup-opt-2、T_sup-opt+2Then, each optimized parameter random value is arranged and combined again to obtain 5⁴Respectively acquiring trans-critical CO of the new energy automobile under each condition₂Refrigerating capacity Q of air conditioning system_cAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step three, if the results obtained in the step two do not satisfy Q_c≥Q_c0、T_out≤T_out0Then, let i equal to 3 again, and then the four optimization parameters are increased by two values, i.e. P_h-opt-3、P_h-opt+3、V_gasc-opt-3、V_gasc-opt+3、T_e-opt-3、T_e-opt+3、T_sup-opt-3、T_sup-opt+3Respectively having seven values, and then, carrying out permutation and combination on each optimized parameter random value again to obtain 7⁴Under different conditions, respectively acquiring trans-critical CO of the new energy automobile under each condition₂Refrigerating capacity Q of air conditioning system_cAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step four, if the results obtained in the step three do not satisfy Q_c≥Q_c0、T_out≤T_out0Increasing the gradient value and taking the delta P_h1＝2 △P_h，△V_gasc1＝2△V_gasc、△T_e1＝2△T_e、△T_sup1＝2△T_supRepeating the above steps one, two and three, if Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step five, if the results obtained in the step four do not satisfy Q_c≥Q_c0、T_out≤T_out0If so, the gradient value is increased again, and Δ P is taken_h2＝4 △P_h，△V_gasc2＝4△V_gasc、△T_e2＝4△T_e、△T_sup2＝4△T_supRepeating the above steps one, two and three, if Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step six, if the results obtained in the step five do not satisfy Q_c≥Q_c0、T_out≤T_out0The air conditioning system is unreasonable in design and does not have the optimal working condition meeting the conditions of refrigerating capacity, heating capacity and air outlet temperature.

Further, in the winter heating mode: the output quantity of the control method is searched by a multi-parameter extremum: optimum operating high pressure P_h-optOptimum air volume V of external heat exchanger_gasc-optOptimum evaporation temperature T_e-optAnd an optimum effective superheat T_sup-optRespectively acquiring the heating capacity Q of the air conditioning system as an initial value_hAnd the air-conditioner air-out temperature T_out；

If the heating quantity and the air outlet temperature do not satisfy Q_c≥Q_c0，T_out≥T_out0Then by Δ P_h＝0.1MPa，△V_gasc＝10m³/h、△ T_e＝0.2℃、△T_supTaking the ith order value of four optimized parameters as gradient at 0.2 ℃: p_h-opt-i、V_gasc-opt-i、T_e-opt-i、 T_sup-opt-iAnd P_h-opt+i、V_gasc-opt+i、T_e-opt+i、T_sup-opt+i(ii) a The value is determined by the following formula:

P_h-opt-i＝P_h-opt-i·ΔP_h

V_gasc-opt-i＝V_gasc-opt-i·ΔV_gasc

T_e-opt-i＝T_e-opt-i·ΔT_e

T_sup-opt-i＝T_sup-opt-i·ΔT_sup

P_h-opt+i＝P_h-opt+i·ΔP_h

V_gasc-opt+i＝V_gasc-opt+i·ΔV_gasc

T_e-opt+i＝T_e-opt+i·ΔT_e

T_sup-opt+i＝T_sup-opt+i·ΔT_sup

wherein i is 1,2,3

Step one, when i is equal to 1, the four optimization parameters respectively have 3 values, namely P_h-opt、P_h-opt-1、P_h-opt+1、V_gasc-opt、V_gasc-opt-1、 V_gasc-opt+1、T_e-opt、T_e-opt-1、T_e-opt+1、T_sup-opt、T_sup-opt-1、T_sup-opt+1And arranging and combining random values of each optimized parameter to obtain 3⁴Respectively acquiring trans-critical CO of the new energy automobile under each condition₂Heating capacity Q of air conditioning system_hAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step two, if the results obtained in the step one do not satisfy Q_c≥Q_c0，T_out≥T_out0Then, let i be 2 again, and then the four optimization parameters are increased by two values: p_h-opt-2、P_h-opt+2、V_gasc-opt-2、V_gasc-opt+2、T_e-opt-2、T_e-opt+2、T_sup-opt-2、T_sup-opt+2Respectively have five values, and then each optimized parameter is randomly selected again to obtain 5 values⁴Under different conditions, respectively acquiring trans-critical CO of the new energy automobile under each condition₂Heating capacity Q of air conditioning system_hAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step three, if the results obtained in the step two do not satisfy Q_c≥Q_c0，T_out≥T_out0Then, let i be 3 again, and then the four optimization parameters are increased by two values: p_h-opt-3、P_h-opt+3、V_gasc-opt-3、V_gasc-opt+3、T_e-opt-3、T_e-opt+3、T_sup-opt-3、T_sup-opt+3Respectively, have seven values, and then are respectively used for each excelRandomly taking values of chemical parameters to carry out permutation and combination to obtain 7 in total⁴Under different conditions, respectively acquiring trans-critical CO of the new energy automobile under each condition₂Heating capacity Q of air conditioning system_hAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step four, if the results obtained in the step three do not satisfy Q_c≥Q_c0，T_out≥T_out0Increasing the gradient value and taking the delta P_h1＝2 △P_h，△V_gasc1＝2△V_gasc、△T_e1＝2△T_e、△T_sup1＝2△T_supRepeating the above steps if Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step five, if the results obtained in the step four do not satisfy Q_c≥Q_c0，T_out≥T_out0If so, the gradient value is increased again, and Δ P is taken_h2＝4 △P_h，△V_gasc2＝4△V_gasc、△T_e2＝4△T_e、△T_sup2＝4△T_supRepeating the above steps if Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step six, if the results obtained in the step five do not satisfy Q_c≥Q_c0，T_out≥T_out0The air conditioning system is unreasonable in design and does not have the optimal working condition meeting the conditions of refrigerating capacity, heating capacity and air outlet temperature.

Further, the new energy automobile transcritical CO₂Air conditioning system heating mode in winterCoefficient of performance COP_hThe calculation formula of (a) is as follows:

COP_hthe performance coefficient of the air conditioning system in the heating mode in winter is unitless;

Q_hthe unit is the heating capacity of the air conditioning system, KW;

W_cthe unit is KW for the power consumption of a compressor of an air conditioning system;

W_fthe total power consumption of the fans of the heat exchangers inside and outside the vehicle of the air conditioning system is in KW unit.

Further, the new energy automobile transcritical CO₂Coefficient of performance COP of air conditioning system in summer refrigeration mode_cThe calculation formula of (a) is as follows:

COP_cthe performance coefficient of the air-conditioning system in the summer refrigeration mode is zero;

Q_cthe unit is the heating capacity of the air conditioning system, KW;

W_cthe unit is KW for the power consumption of a compressor of an air conditioning system;

W_fthe total power consumption of the fans of the heat exchangers inside and outside the vehicle of the air conditioning system is in KW unit.

Further, the three-way valve is an opening adjustable valve;

obtaining the optimal operation high pressure value P of the system_h-optAir volume V of external heat exchanger_gasc-optEvaporation temperature T_e-optAnd effective superheat T_sup-optThen, controlling and controlling the new energy automobile to transcritical CO₂The air conditioning system operates under the working condition of an optimal value;

wherein, the transcritical CO of the new energy automobile is controlled₂Operating high pressure value P of air conditioning system_hAir volume V of external heat exchanger controlled by electronic expansion valve_gascBy changing from outside to outsideFan control and evaporation temperature T of heater_eThe effective superheat T is controlled by the rotation speed of the compressor_sup-optControlled by the mass flow through the regenerator; the refrigerant flow passing through the heat regenerator is adjusted by adjusting the opening degree of the three-way valve, so that the superheat degree is controlled.

Compared with the prior art, the invention has the following beneficial effects:

1. the new energy automobile air conditioner refrigerant is mainly R134a, has poor environmental protection performance and gradually faces to be eliminated. The new energy automobile air conditioning system adopts the natural working medium carbon dioxide as the refrigerant, and is environment-friendly;

2. the invention firstly provides a control system which combines a multi-parameter extremum search control algorithm with a self-learning neural network, optimizes four optimized parameters of the air conditioning system, and then further provides a specific control strategy of the four optimized parameters.

3. The air conditioner of the new energy automobile can be rapidly self-regulated all the time under various changeable and complex driving environment working conditions, the comfort requirement of passengers on a carriage is met under the lowest energy consumption in the shortest time, and the future energy crisis is relieved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:

FIG. 1 shows transcritical CO of the new energy automobile₂The structure schematic diagram of the air conditioning system;

FIG. 2 shows transcritical CO of the new energy automobile₂A logic block diagram of a multi-target multi-parameter optimization control method of the air conditioning system;

wherein: the system comprises a compressor 1, a four-way reversing valve 2, an in-vehicle heat exchanger 3, a heat regenerator 4, an electronic expansion valve 5, an out-vehicle heat exchanger 6, a three-way valve 7 and a reservoir 8.

Detailed Description

The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.

The following detailed description is exemplary in nature and is intended to provide further details of the invention. Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention.

The present invention will be described in further detail with reference to the accompanying drawings.

Referring to fig. 1, the invention provides a new energy vehicle transcritical CO₂An air conditioning system, comprising essentially the following components: the system comprises a compressor 1, a four-way reversing valve 2, an in-vehicle heat exchanger 3, a heat regenerator 4, an electronic expansion valve 5, an out-vehicle heat exchanger 6, a three-way valve 7 and a liquid storage device 8. The outlet of the compressor 1 is connected with the port d of the four-way reversing valve 2, the port a of the four-way reversing valve 2 is connected with one end of the heat exchanger 6 outside the vehicle, the port c of the four-way reversing valve 2 is sequentially connected with the heat exchanger 3 inside the vehicle, the electronic expansion valve 5, the first heat exchange pipeline of the heat regenerator 4 and the other end of the heat exchanger 6 outside the vehicle, the port b of the four-way reversing valve 2 is connected with the port c of the three-way valve 7, the port a of the three-way valve 7 is connected with the inlet of the liquid accumulator 8 through the second heat exchange pipeline of the heat regenerator 4, the port b of the three-way valve 7 is connected with the inlet of the liquid accumulator 8 together with.

In the summer refrigeration working condition, the port a and the port d of the four-way reversing valve 2 are communicated, the port b is communicated with the port c, the port a and the port c of the three-way valve 7 are communicated, the port b is closed, refrigerant is compressed to a high-temperature high-pressure state in the compressor 1, enters the outdoor heat exchanger 6 through the port d and the port a of the four-way reversing valve 2, enters the high-pressure inlet of the heat regenerator 4 after exchanging heat with air, exchanges heat with low-temperature fluid in the low-pressure channel of the heat regenerator 4, is throttled by the electronic expansion valve 5 to become low-temperature low-pressure two-phase fluid, flows to the in-vehicle heat exchanger 3, exchanges heat with air to provide cold for a carriage and reduce the temperature of the carriage, then flows into the port c of the three-way valve 7 through the port c and the port b of the four-way reversing valve 2, flows to the low-pressure inlet of the heat regenerator 4 from the port a of the port a, and finally back to the suction side of the compressor 1.

When the four-way reversing valve 2 is in a heating working condition in winter, the port c is communicated with the port d, the port a is communicated with the port b, the port c is communicated with the port b of the three-way valve 7, the port a is closed, a refrigerant is compressed to a high-temperature high-pressure state in the compressor 1, enters the in-vehicle heat exchanger 3 through the port d and the port c of the four-way reversing valve 2, exchanges heat with air, provides heat for a carriage, raises the temperature of the carriage, becomes low-temperature low-pressure two-phase fluid after being throttled by the electronic expansion valve 5, enters the high-pressure inlet of the heat regenerator 4, and the refrigerant basically has no heat exchange in the heat regenerator because a low-pressure channel of the heat regenerator 4 is bypassed. After continuously flowing to the exterior heat exchanger 6 to exchange heat with the environment, the refrigerant flows into the port c of the three-way valve 7 through the ports a and b of the four-way reversing valve 2, then enters the liquid storage device 8 from the port b of the three-way valve 7, and finally returns to the air suction end of the compressor 1.

New energy automobile trans-critical CO₂The air-conditioning heat pump system comprises the following four target parameters: coefficient of performance, cooling capacity, heating capacity and air conditioner outlet air temperature (T) of air conditioning system_out) (ii) a And the following four optimization parameters: operating high pressure value (P) of the system_h) And the air volume (V) of the exterior heat exchanger 6_gascEvaporation temperature T_eAnd effective superheat T_sup). The four target parameters are target quantities of the multivariable extremum search control method, and the four optimization parameters are control quantities of the multivariable extremum search control method. Because the air conditioning system mainly has two modes of summer refrigeration and winter heating, the specific control logic is divided into the following two types according to the functions of the air conditioning system:

when the transcritical carbon dioxide new energy automobile air conditioner is in a summer refrigeration mode: the target quantities of the multivariable extremum searching control system are respectively the performance coefficient (COP value) and the cooling capacity (Q) of the air conditioning system_c) And air conditioner outlet air temperature (T)_out) The control quantity is the running high pressure value (P) of the system_h) Of heat exchangers external to the vehicleAir volume (V)_gasc) Evaporation temperature (T)_e) And effective superheat (T)_sup). Cooling capacity (Q) of air conditioning system_c) And air conditioner outlet air temperature (T)_out) Set by manufacturer or user, respectively, as Q_c0And T_out0The multivariable extremum searching control system meets the condition that the refrigerating capacity is not lower than the set value (namely Q)_c≥Q_c0) And the outlet air temperature is not higher than the set value (namely T)_out≤T_out0) And finding the optimal values of the four control variables when the COP (coefficient of performance) of the system reaches the maximum value.

When the transcritical carbon dioxide new energy automobile air conditioner is in a winter heating mode: the target quantities of the multivariable extremum searching control system are respectively the coefficient of performance (COP value) and the heating capacity (Q) of the air conditioning system_h) And air conditioner outlet air temperature (T)_out) The control quantity is the running high pressure value (P) of the system_h) Air volume (V) of external heat exchanger_gasc) Evaporation temperature (T)_e). Heating capacity (Q) of air conditioning system_h) And air conditioner outlet air temperature (T)_out) Set by manufacturer or user, respectively, as Q_h0And T_out0The multivariable extremum searching control system meets the premise that the heating quantity and the air outlet temperature are not lower than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) And finding the optimal values of the four control variables when the COP (coefficient of performance) of the system reaches the maximum value.

The multi-parameter extremum search control is to search the extremum of multiple variables at the same time in the variable search process, so as to find the best performance air conditioning system input problem under any condition, namely:

(P_h-opt(t),V_gasc-opt(t),T_e-opt(t)，T_sup-opt(t))＝argminf(P_h，P_l,V_gasc,T_e,T_sup,t)

wherein: p_h，V_gasc,T_e，T_supRespectively input control variables of the control system;

P_h-opt(t),V_gasc-opt(t),T_e-opt(t),T_sup-opt(t) respectively searching for a merit value for the output of the control system;

f(P_h，V_gasc,T_e,T_supand t) is a non-linear system performance function for static or slow time-varying.

The multi-parameter extremum search control can only optimize for a single target, that is, only find out the optimal optimized parameter value when the COP is maximum, so that it cannot be ensured whether the refrigeration/heat and the outlet air temperature of the air conditioning system meet the requirements. Therefore, an additional self-learning neural network is needed, and the specific control logic is as follows:

referring to fig. 2, when the transcritical carbon dioxide new energy automobile air conditioner is in the summer cooling mode: optimum operating high voltage (P) with multi-parameter extremum search control method output_h-opt) Optimum external heat exchanger air volume (V)_gasc-opt) Optimum evaporation temperature (T)_e-opt) And an optimum effective superheat (T)_sup-opt) Respectively obtaining the refrigerating capacity (Q) of the air conditioning system as an initial value_c) And air conditioner outlet air temperature (T)_out) If the refrigerating capacity is not less than the set value (i.e. Q) under the condition of not meeting the refrigerating capacity_c≥Q_c0) The outlet air temperature is not higher than the set value (namely T)_out≤T_out0) Then by Δ P_h＝0.1MPa，△V_gasc＝10m³/h、△T_e＝0.2℃、△T_supGradient of 0.2 deg.C, and taking ith order value of four optimized parameters, i.e. P_h-opt-i、V_gasc-opt-i、T_e-opt-i、T_sup-opt-iAnd P_h-opt+i、V_gasc-opt+i、T_e-opt+i、T_sup-opt+i。

The value is determined by the following formula:

P_h-opt-i＝P_h-opt-i·ΔP_h

V_gasc-opt-i＝V_gasc-opt-i·ΔV_gasc

T_e-opt-i＝T_e-opt-i·ΔT_e

T_sup-opt-i＝T_sup-opt-i·ΔT_sup

P_h-opt+i＝P_h-opt+i·ΔP_h

V_gasc-opt+i＝V_gasc-opt+i·ΔV_gasc

T_e-opt+i＝T_e-opt+i·ΔT_e

T_sup-opt+i＝T_sup-opt+i·ΔT_sup

wherein i is 1,2,3

When i is 1, the four optimization parameters respectively have 3 values, namely P_h-opt、P_h-opt-1、P_h-opt+1、V_gasc-opt、V_gasc-opt-1、V_gasc-opt+1、 T_e-opt、T_e-opt-1、T_e-opt+1、T_sup-opt、T_sup-opt-1、T_sup-opt+1Randomly taking values of each optimized parameter, and carrying out permutation and combination for 3⁴The condition, respectively obtaining the refrigerating capacity (Q) of the air conditioning system in each condition_c) And air conditioner outlet air temperature (T)_out) If the refrigerating capacity is not lower than the set value (i.e. Q)_c≥Q_c0) The outlet air temperature is not higher than the set value (namely T)_out≤T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the refrigerating capacity is not less than the set value (namely Q)_c≥Q_c0) The outlet air temperature is not higher than the set value (namely T)_out≤T_out0) Then, let i equal to 2 again, and then the four optimization parameters are increased by two values, i.e. P_h-opt-2、P_h-opt+2、V_gasc-opt-2、V_gasc-opt+2、 T_e-opt-2、T_e-opt+2、T_sup-opt-2、T_sup-opt+2Respectively taking five values, randomly taking values of each optimized parameter again, and performing permutation and combination, wherein the total number is 5⁴The condition, respectively obtaining the refrigerating capacity (Q) of the air conditioning system in each condition_c) And air conditioner outlet air temperature (T)_out) If the refrigerating capacity is not lower than the set value (i.e. Q)_c≥Q_c0) And the outlet air temperature is not higher than the set value (namely T)_out≤T_out0)，Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP corresponding to the working conditions meeting the conditions;

if the refrigerating capacity is not less than the set value (namely Q)_c≥Q_c0) The outlet air temperature is not higher than the set value (namely T)_out≤T_out0) Then, let i equal to 3 again, and then the four optimization parameters are increased by two values, i.e. P_h-opt-3、P_h-opt+3、V_gasc-opt-3、V_gasc-opt+3、 T_e-opt-3、T_e-opt+3、T_sup-opt-3、T_sup-opt+3Respectively having seven values, randomly taking values of each optimized parameter again, and performing permutation and combination to obtain 7⁴The condition, respectively obtaining the refrigerating capacity (Q) of the air conditioning system in each condition_c) And air conditioner outlet air temperature (T)_out) If the refrigerating capacity is not lower than the set value (i.e. Q)_c≥Q_c0) And the outlet air temperature is not higher than the set value (namely T)_out≤T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the refrigerating capacity is not less than the set value (namely Q)_c≥Q_c0) The outlet air temperature is not higher than the set value (namely T)_out≤T_out0) Increasing the gradient value and taking the delta P_h1＝2△P_h，△V_gasc1＝2△V_gasc、△T_e1＝2△T_e、△T_sup1＝2△T_supRepeating the above steps, if the refrigerating capacity is not lower than the set value (namely Q)_c≥Q_c0) And the outlet air temperature is not higher than the set value (namely T)_out≤T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the refrigerating capacity is not less than the set value (namely Q)_c≥Q_c0) The outlet air temperature is not higher than the set value (namely T)_out≤T_out0) If so, the gradient value is increased again, and Δ P is taken_h2＝4△P_h，△V_gasc2＝4△V_gasc、△T_e2＝4△T_e、△T_sup2＝4△T_supRepeating the above steps, if the refrigerating capacity is not lower than the set value (namely Qc is more than or equal to Q)_c0) And the outlet air temperature is not higher than the set value (namely T)_out≤T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the refrigerating capacity is not less than the set value (namely Q)_c≥Q_c0) The outlet air temperature is not higher than the set value (namely T)_out≤T_out0) If the air conditioning system is not designed reasonably, the optimal working condition which meets the conditions of refrigerating capacity, heating capacity and air outlet temperature does not exist, and component design needs to be carried out again.

When the transcritical carbon dioxide new energy automobile air conditioner is in a winter heating mode: optimum operating high voltage (P) with multi-parameter extremum search control method output_h-opt) Optimum external heat exchanger air volume (V)_gasc-opt) Optimum evaporation temperature (T)_e-opt) And an optimum effective superheat (T)_sup-opt) Respectively acquiring the heating capacity (Q) of the air conditioning system as an initial value_h) And air conditioner outlet air temperature (T)_out) If the refrigerating capacity and the outlet air temperature do not satisfy the heating capacity and the outlet air temperature are not lower than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Then by Δ P_h＝0.1MPa，△V_gasc＝10m³/h、△T_e＝0.2℃、△T_supGradient of 0.2 deg.C, and taking ith order value of four optimized parameters, i.e. P_h-opt-i、V_gasc-opt-i、T_e-opt-i、T_sup-opt-iAnd P_h-opt+i、V_gasc-opt+i、T_e-opt+i、T_sup-opt+i. The value is determined by the following formula:

P_h-opt-i＝P_h-opt-i·ΔP_h

V_gasc-opt-i＝V_gasc-opt-i·ΔV_gasc

T_e-opt-i＝T_e-opt-i·ΔT_e

T_sup-opt-i＝T_sup-opt-i·ΔT_sup

P_h-opt+i＝P_h-opt+i·ΔP_h

V_gasc-opt+i＝V_gasc-opt+i·ΔV_gasc

T_e-opt+i＝T_e-opt+i·ΔT_e

T_sup-opt+i＝T_sup-opt+i·ΔT_sup

wherein i is 1,2,3

When i is 1, the four optimization parameters respectively have 3 values, namely P_h-opt、P_h-opt-1、P_h-opt+1、V_gasc-opt、V_gasc-opt-1、V_gasc-opt+1、 T_e-opt、T_e-opt-1、T_e-opt+1、T_sup-opt、T_sup-opt-1、T_sup-opt+1Randomly taking values of each optimized parameter, and carrying out permutation and combination for 3⁴The heating capacity (Q) of the air conditioning system is acquired separately for each case_h) And air conditioner outlet air temperature (T)_out) If the heating quantity and the air outlet temperature are not lower than the set value (namely Q) under the condition of meeting the requirement_c≥Q_c0，T_out≥T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the heating quantity and the outlet air temperature are not less than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Then, let i equal to 2 again, and then the four optimization parameters are increased by two values, i.e. P_h-opt-2、P_h-opt+2、V_gasc-opt-2、V_gasc-opt+2、T_e-opt-2、T_e-opt+2、T_sup-opt-2、 T_sup-opt+2Respectively taking five values, randomly taking values of each optimized parameter again, and performing permutation and combination, wherein the total number is 5⁴The heating capacity (Q) of the air conditioning system is acquired separately for each case_h) And air conditioner outlet air temperature (T)_out)，If the heating quantity and the air outlet temperature are not lower than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the heating quantity and the outlet air temperature are not less than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Then, let i equal to 3 again, and then the four optimization parameters are increased by two values, i.e. P_h-opt-3、P_h-opt+3、V_gasc-opt-3、V_gasc-opt+3、T_e-opt-3、T_e-opt+3、T_sup-opt-3、 T_sup-opt+3Respectively having seven values, randomly taking values of each optimized parameter again, and performing permutation and combination to obtain 7⁴The heating capacity (Q) of the air conditioning system is acquired separately for each case_h) And air conditioner outlet air temperature (T)_out) If the heating quantity and the air outlet temperature are not lower than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the heating quantity and the outlet air temperature are not less than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Increasing the gradient value and taking the delta P_h1＝2△P_h，△V_gasc1＝2△V_gasc、△T_e1＝2△T_e、△T_sup1＝2△T_supRepeating the above steps, if the requirement of the first claim is satisfied, namely the heating quantity and the outlet air temperature are not lower than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the heating quantity and the outlet air temperature are not less than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Then, thenIncreasing the gradient value again, taking Delta P_h2＝4△P_h，△V_gasc2＝4△V_gasc、△T_e2＝4△T_e、△T_sup2＝4△T_supRepeating the steps, and if the heating quantity and the air outlet temperature are not lower than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) Outputting the four optimized parameter values of the group, and if the multiple groups of working conditions meet the conditions, outputting the group with the largest COP in the working conditions meeting the conditions;

if the heating quantity and the outlet air temperature are not less than the set value (namely Q)_c≥Q_c0，T_out≥T_out0) If the air conditioning system is not designed reasonably, the optimal working condition which meets the conditions of refrigerating capacity, heating capacity and air outlet temperature does not exist, and component design needs to be carried out again.

In the present invention, the parameter values, e.g. P, are optimized for each set_h-opt、V_gasc-opt、T_e-opt、T_sup-optObtaining heating capacity (Q) of air conditioning system_h) And air conditioner outlet air temperature (T)_out) The method comprises the following steps: the air volume of the heat exchanger in the automobile of the automobile air conditioner is set by a manufacturer, and a user selects the air volume. Therefore, when the air conditioning system fixes the four parameters and the air inlet quantity in the vehicle, the system circulation can be obtained by dynamic simulation or user database query. Wherein the refrigerating capacity (Q)_c) And heat production quantity (Q)_h) And air conditioner outlet air temperature (T)_out) The three are all the intrinsic parameters of the system and are determined by the system. The calculation formula of the coefficient of performance (i.e., COP value) of the air conditioning system is as follows:

wherein: COP_hThe performance of the air conditioning system in the heating mode in winter is unitless;

Q_hthe unit is the heating capacity of the air conditioning system, KW;

W_cthe unit is KW for the power consumption of a compressor of an air conditioning system;

W_fthe total power consumption of fans of the internal and external heat exchangers of the air conditioning system is KW;

COP_cthe performance of the air conditioning system in a summer refrigeration mode is zero;

Q_cthe unit is the heating capacity of the air conditioning system, KW;

in the present invention, the three-way valve 7 is an opening-adjustable valve. When the multivariable extremum searching control system is optimized, the optimal operation high pressure value (P) of the system is obtained_h-opt) Air volume (V) of external heat exchanger_gasc-opt) Evaporation temperature (T)_e-opt) And effective superheat (T)_sup-opt) And then controlling the air conditioning system to operate under the working condition of the optimal value. Wherein the operating high pressure value (P) of the system_h) The air quantity (V) of the external heat exchanger is controlled by the opening degree of the throttle valve_gasc) The evaporation temperature (T) is controlled by a fan of the heat exchanger outside the vehicle_e) Effective superheat (T) controlled by the speed of the compressor_sup-opt) The mass flow through the heat regenerator is used for controlling, namely the refrigerant flow passing through the heat regenerator is adjusted by adjusting the opening degree of the three-way valve 7, thereby achieving the purpose of controlling the superheat degree.

It will be appreciated by those skilled in the art that the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The embodiments disclosed above are therefore to be considered in all respects as illustrative and not restrictive. All changes which come within the scope of or equivalence to the invention are intended to be embraced therein.

Claims (3)

1. Transcritical CO₂The optimal control method of the air-conditioning heat pump system is characterized by being based on a transcritical CO₂An air conditioning heat pump system; the trans-critical CO₂Air conditioner heat pump system includes: the system comprises a compressor (1), a four-way reversing valve (2), an in-vehicle heat exchanger (3), a heat regenerator (4), an electronic expansion valve (5), an out-vehicle heat exchanger (6), a three-way valve (7) and a liquid storage device (8);an outlet of a compressor (1) is connected with a port d of a four-way reversing valve (2), a port a of the four-way reversing valve (2) is connected with one end of an external heat exchanger (6), a port c of the four-way reversing valve (2) is sequentially connected with an internal heat exchanger (3), an electronic expansion valve (5), a first heat exchange pipeline of a heat regenerator (4) and the other end of the external heat exchanger (6), a port b of the four-way reversing valve (2) is connected with a port c of a three-way valve (7), a port a of the three-way valve (7) is connected with an inlet of a liquid accumulator (8) through a second heat exchange pipeline of the heat regenerator (4), the port b of the three-way valve (7) and the second heat exchange pipeline of the heat regenerator (4) are jointly connected with an inlet of the liquid accumulator (8), and an outlet;

the optimization control method adopts a multivariable extremum search control method for optimization, and comprises the following steps:

four target parameters: coefficient of performance COP value and refrigerating capacity Q of air conditioning system_cHeating capacity Q_hAnd the air-conditioner air-out temperature T_out；

Four optimization parameters: operating high pressure value P of air conditioning system_hAir volume V of external heat exchanger_gascEvaporation temperature T_eAnd effective superheat T_sup；

The four target parameters are target quantities of the multivariable extremum search control method, and the four optimized parameters are control quantities of the multivariable extremum search control method;

in the cooling mode in summer: the target quantities of the multivariable extremum search control method are respectively the performance coefficient COP value and the refrigerating capacity Q of the air conditioning system_cAnd the air outlet temperature T of the air conditioner_outThe control quantity is the running high-pressure value P of the system_hAir volume V of external heat exchanger_gascEvaporation temperature T_eAnd effective superheat T_sup(ii) a Refrigerating capacity Q of air conditioning system_cAnd the air-conditioner air-out temperature T_outAre respectively Q_c0And T_out0The multivariable extremum searching control method searches for the optimal values of the four control variables when the performance parameter COP of the system reaches the maximum value on the premise that the refrigerating capacity is not lower than a set value; and controlling the new energy automobile trans-critical CO by an optimal value₂Operating an air conditioning system;

in the winter heating mode: multivariate extreme value searchThe target quantities of the cable control method are respectively a coefficient of performance COP value and a heating quantity Q of the air conditioning system_hAnd the air-conditioner air-out temperature T_outThe control quantity is the running high-pressure value P of the system_hAir volume V of external heat exchanger_gascEvaporation temperature T_eAnd effective superheat T_sup(ii) a Heating capacity Q of air conditioning system_hAnd the air-conditioner air-out temperature T_outAre respectively Q_h0And T_out0The multivariable extreme value search control system finds the optimal values of the four control variables when the performance parameter COP of the system reaches the maximum value on the premise that the heating capacity and the air outlet temperature are not lower than set values; and controlling the new energy automobile trans-critical CO by an optimal value₂Operating an air conditioning system;

new energy automobile trans-critical CO₂Coefficient of performance COP of air conditioning system in winter heating mode_hThe calculation formula of (a) is as follows:

COP_hthe performance coefficient of the air conditioning system in the heating mode in winter is unitless;

Q_hthe unit is the heating capacity of the air conditioning system, KW;

W_cthe unit is KW for the power consumption of a compressor of an air conditioning system;

W_fthe total power consumption of fans of the internal and external heat exchangers of the air conditioning system is KW;

new energy automobile trans-critical CO₂Coefficient of performance COP of air conditioning system in summer refrigeration mode_cThe calculation formula of (a) is as follows:

COP_cthe performance coefficient of the air-conditioning system in the summer refrigeration mode is zero;

Q_cthe unit is the heating capacity of the air conditioning system, KW;

W_cthe unit is KW for the power consumption of a compressor of an air conditioning system;

W_fthe total power consumption of fans of the internal and external heat exchangers of the air conditioning system is KW;

in the variable searching process, the extreme values of a plurality of variables are optimized simultaneously, and the input problem of the air conditioning system with the best performance under any condition is found out:

(P_h-opt(t),V_gasc-opt(t),T_e-opt(t)，T_sup-opt(t))＝argminf(P_h，P_l,V_gasc,T_e,T_sup,t)

wherein: p_h，V_gasc,T_e，T_supRespectively are input control variables;

P_h-opt(t),V_gasc-opt(t),T_e-opt(t),T_sup-opt(t) output merit values, respectively;

f(P_h，V_gasc,T_e,T_supt) is a nonlinear system performance function for static or slow time-varying;

the three-way valve (7) is an opening adjustable valve;

obtaining the optimal operation high pressure value P of the system_h-optAir volume V of external heat exchanger_gasc-optEvaporation temperature T_e-optAnd effective superheat T_sup-optThen, controlling and controlling the new energy automobile to transcritical CO₂The air conditioning system operates under the working condition of an optimal value;

wherein, the transcritical CO of the new energy automobile is controlled₂Operating high pressure value P of air conditioning system_hThe air volume V of the heat exchanger (6) outside the vehicle is controlled by the electromagnetic expansion valve (5)_gascThe evaporation temperature T is controlled by a fan of the heat exchanger (6) outside the vehicle_eThe effective superheat T is controlled by the rotating speed of the compressor (1)_sup-optControlled by the mass flow through the regenerator (4); the refrigerant flow passing through the heat regenerator (4) is adjusted by adjusting the opening degree of the three-way valve (7), thereby controlling the superheat degree.

2. The optimization control method according to claim 1, characterized in thatAnd in the summer refrigeration mode: high pressure P for optimum operation of output using multivariate extreme search control method_h-optOptimal air volume V of external heat exchanger_gasc-optOptimum evaporation temperature T_e-optAnd an optimum effective superheat T_sup-optRespectively obtaining the refrigerating capacity Q of the air conditioning system as an initial value_cAnd the air-conditioner air-out temperature T_out；

If the refrigerating capacity and the outlet air temperature do not satisfy Q_c≥Q_c0、T_out≤T_out0Then by Δ P_h＝0.1MPa，△V_gasc＝10m³/h、△T_e＝0.2℃、△T_supGradient of 0.2 deg.C, and taking ith order value of four optimized parameters, i.e. P_h-opt-i、V_gasc-opt-i、T_e-opt-i、T_sup-opt-iAnd P_h-opt+i、V_gasc-opt+i、T_e-opt+i、T_sup-opt+i；

The value is determined by the following formula:

P_h-opt-i＝P_h-opt-i·ΔP_h

V_gasc-opt-i＝V_gasc-opt-i·ΔV_gasc

T_e-opt-i＝T_e-opt-i·ΔT_e

T_sup-opt-i＝T_sup-opt-i·ΔT_sup

P_h-opt+i＝P_h-opt+i·ΔP_h

V_gasc-opt+i＝V_gasc-opt+i·ΔV_gasc

T_e-opt+i＝T_e-opt+i·ΔT_e

T_sup-opt+i＝T_sup-opt+i·ΔT_sup

wherein i is 1,2,3

Step one, when i is equal to 1, four optimization parameters respectively have 3 values: p_h-opt、P_h-opt-1、P_h-opt+1、V_gasc-opt、V_gasc-opt-1、V_gasc-opt+1、T_e-opt、T_e-opt-1、T_e-opt+1、T_sup-opt、T_sup-opt-1、T_sup-opt+1Randomly dereferencing each optimized parameter, and performing permutation and combination to obtain 3 in total⁴Respectively acquiring trans-critical CO of the new energy automobile under each condition₂Refrigerating capacity Q of air conditioning system_cAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step two, if the results obtained in the step one do not satisfy Q_c≥Q_c0、T_out≤T_out0If i is equal to 2, then the four optimization parameters are increased by two values, i.e. P_h-opt-2、P_h-opt+2、V_gasc-opt-2、V_gasc-opt+2、T_e-opt-2、T_e-opt+2、T_sup-opt-2、T_sup-opt+2Then, each optimized parameter random value is arranged and combined again to obtain 5⁴Respectively acquiring trans-critical CO of the new energy automobile under each condition₂Refrigerating capacity Q of air conditioning system_cAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step three, if the results obtained in the step two do not satisfy Q_c≥Q_c0、T_out≤T_out0Then, let i equal to 3 again, and then the four optimization parameters are increased by two values, i.e. P_h-opt-3、P_h-opt+3、V_gasc-opt-3、V_gasc-opt+3、T_e-opt-3、T_e-opt+3、T_sup-opt-3、T_sup-opt+3Respectively having seven values, and then, carrying out permutation and combination on each optimized parameter random value again to obtain 7⁴Under different conditions, respectively acquiring trans-critical CO of the new energy automobile under each condition₂Refrigerating capacity Q of air conditioning system_cAnd air conditioner outlet airTemperature T_outIf Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step four, if the results obtained in the step three do not satisfy Q_c≥Q_c0、T_out≤T_out0Increasing the gradient value and taking the delta P_h1＝2△P_h，△V_gasc1＝2△V_gasc、△T_e1＝2△T_e、△T_sup1＝2△T_supRepeating the above steps one, two and three, if Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step five, if the results obtained in the step four do not satisfy Q_c≥Q_c0、T_out≤T_out0If so, the gradient value is increased again, and Δ P is taken_h2＝4△P_h，△V_gasc2＝4△V_gasc、△T_e2＝4△T_e、△T_sup2＝4△T_supRepeating the above steps one, two and three, if Q is satisfied_c≥Q_c0、T_out≤T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step six, if the results obtained in the step five do not satisfy Q_c≥Q_c0、T_out≤T_out0The air conditioning system is unreasonable in design and does not have the optimal working condition meeting the conditions of refrigerating capacity, heating capacity and air outlet temperature.

3. The optimal control method according to claim 1, wherein in the winter heating mode: the output quantity of the control method is searched by a multi-parameter extremum: optimum operating high pressure P_h-optOptimum air volume of external heat exchangerV_gasc-optOptimum evaporation temperature T_e-optAnd an optimum effective superheat T_sup-optRespectively acquiring the heating capacity Q of the air conditioning system as an initial value_hAnd the air-conditioner air-out temperature T_out；

If the heating quantity and the air outlet temperature do not satisfy Q_c≥Q_c0，T_out≥T_out0Then by Δ P_h＝0.1MPa，△V_gasc＝10m³/h、△T_e＝0.2℃、△T_supTaking the ith order value of four optimized parameters as gradient at 0.2 ℃: p_h-opt-i、V_gasc-opt-i、T_e-opt-i、T_sup-opt-iAnd P_h-opt+i、V_gasc-opt+i、T_e-opt+i、T_sup-opt+i(ii) a The value is determined by the following formula:

P_h-opt-i＝P_h-opt-i·ΔP_h

V_gasc-opt-i＝V_gasc-opt-i·ΔV_gasc

T_e-opt-i＝T_e-opt-i·ΔT_e

T_sup-opt-i＝T_sup-opt-i·ΔT_sup

P_h-opt+i＝P_h-opt+i·ΔP_h

V_gasc-opt+i＝V_gasc-opt+i·ΔV_gasc

T_e-opt+i＝T_e-opt+i·ΔT_e

T_sup-opt+i＝T_sup-opt+i·ΔT_sup

wherein i is 1,2,3

Step one, when i is equal to 1, the four optimization parameters respectively have 3 values, namely P_h-opt、P_h-opt-1、P_h-opt+1、V_gasc-opt、V_gasc-opt-1、V_gasc-opt+1、T_e-opt、T_e-opt-1、T_e-opt+1、T_sup-opt、T_sup-opt-1、T_sup-opt+1And arranging and combining random values of each optimized parameter to obtain 3⁴Situation, obtaining each situation separatelyNew energy automobile trans-critical CO₂Heating capacity Q of air conditioning system_hAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step two, if the results obtained in the step one do not satisfy Q_c≥Q_c0，T_out≥T_out0Then, let i be 2 again, and then the four optimization parameters are increased by two values: p_h-opt-2、P_h-opt+2、V_gasc-opt-2、V_gasc-opt+2、T_e-opt-2、T_e-opt+2、T_sup-opt-2、T_sup-opt+2Respectively have five values, and then each optimized parameter is randomly selected again to obtain 5 values⁴Under different conditions, respectively acquiring trans-critical CO of the new energy automobile under each condition₂Heating capacity Q of air conditioning system_hAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step three, if the results obtained in the step two do not satisfy Q_c≥Q_c0，T_out≥T_out0Then, let i be 3 again, and then the four optimization parameters are increased by two values: p_h-opt-3、P_h-opt+3、V_gasc-opt-3、V_gasc-opt+3、T_e-opt-3、T_e-opt+3、T_sup-opt-3、T_sup-opt+3Respectively having seven values, and then, carrying out permutation and combination on each optimized parameter random value to obtain 7 values⁴Under different conditions, respectively acquiring trans-critical CO of the new energy automobile under each condition₂Heating capacity Q of air conditioning system_hAnd the air-conditioner air-out temperature T_outIf Q is satisfied_c≥Q_c0，T_out≥T_out0Then the set of four optimized parameter values is output, ifIf the multiple groups of working conditions meet the conditions, outputting a group of optimized parameter values with the largest COP corresponding to the working conditions meeting the conditions;

step four, if the results obtained in the step three do not satisfy Q_c≥Q_c0，T_out≥T_out0Increasing the gradient value and taking the delta P_h1＝2△P_h，△V_gasc1＝2△V_gasc、△T_e1＝2△T_e、△T_sup1＝2△T_supRepeating the above steps if Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step five, if the results obtained in the step four do not satisfy Q_c≥Q_c0，T_out≥T_out0If so, the gradient value is increased again, and Δ P is taken_h2＝4△P_h，△V_gasc2＝4△V_gasc、△T_e2＝4△T_e、△T_sup2＝4△T_supRepeating the above steps if Q is satisfied_c≥Q_c0，T_out≥T_out0If the plurality of groups of working conditions meet the conditions, outputting a group of optimized parameter values which correspond to the largest COP in the working conditions meeting the conditions;

step six, if the results obtained in the step five do not satisfy Q_c≥Q_c0，T_out≥T_out0The air conditioning system is unreasonable in design and does not have the optimal working condition meeting the conditions of refrigerating capacity, heating capacity and air outlet temperature.

Images