CN113074952A - Energy consumption testing rack, system and method for power system of plug-in hybrid electric vehicle - Google Patents
Energy consumption testing rack, system and method for power system of plug-in hybrid electric vehicle Download PDFInfo
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Abstract
The embodiment of the invention relates to an energy consumption testing rack, system and method for a power system of a plug-in hybrid electric vehicle. The test bench of the embodiment of the invention comprises an upper computer 3, a real-time simulation system 5, a loading motor 7 and a half-shaft torque sensor 8; the upper computer 3 is used for parameter configuration and display of the test bench, the upper computer 3 receives first signals which are sent by the real-time simulation system 5 and related to the working states of the power system and the high-voltage electrical accessories, and the real-time simulation system 5 sends second signals related to the parameter configuration of the bench to the vehicle control unit 1, the PTC electrical heating system analog load 12 and the electric air conditioning system analog load 14. The embodiment of the invention can realize the test of the energy consumption of the whole vehicle at the initial stage of research and development that the vehicle does not reach the integration of a power system and high-voltage electric accessories, and provides support for the design and development of the economic indexes of the whole vehicle.
Description
Technical Field
The invention relates to an automobile testing technology, in particular to an energy consumption testing rack of a power system of a plug-in hybrid electric vehicle and a testing method thereof.
Background
With the increasing maturity of new energy automobile industrialization, the new energy automobile product accounts for the increase of the automobile output and sales volume year by year, the plug-in hybrid electric vehicle has the advantages of both a pure electric automobile and a hybrid electric automobile, has the characteristics of effectively reducing energy consumption, being free of mileage anxiety and the like, and has become an important way for automobile development in China. Meanwhile, with the increasing fierce grade receding and market competition of new energy automobile subsidies, higher and higher requirements are provided for the performance of new energy automobile products. The performance indexes of the new energy automobile product are numerous, wherein economic indexes such as energy consumption and pure electric driving range are most concerned by consumers, and are important indexes for reflecting automobile model market competitiveness, so that the design and development of the economic indexes are particularly important in the development and design process of the new energy automobile model product.
The nominal energy consumption of the plug-in hybrid electric vehicle on the market is greatly different from the actual running energy consumption, the actual traffic condition cannot be reflected by the testing method of the nominal energy consumption, and the use of electric accessories and the setting of the testing environment temperature are not clear. In the test process aiming at the design and development of economic indexes, when the research and development of a power system are completed or partially completed and the energy economy evaluation of the actual operation working condition needs to be carried out in advance, because the whole vehicle integration of the power system and the high-voltage electrical accessory is not achieved, a bench test method capable of quickly testing the actual road working condition of the hybrid power assembly is needed.
Disclosure of Invention
The embodiment of the invention aims to provide an energy consumption rack of a power system of a plug-in hybrid electric vehicle and a test method thereof, so that the test of the energy consumption of the whole vehicle can be realized at the initial stage of research and development without integration of a power system and high-voltage electric accessories, and support is provided for the design and development of the economic index of the whole vehicle.
A plug-in hybrid vehicle powertrain energy consumption test bench comprising: the system comprises an upper computer 3, a real-time simulation system 5, a loading motor 7 and a half-shaft torque sensor 8;
the upper computer 3 is used for configuring and displaying parameters of the test bench, is connected with the real-time simulation system 5 through test system signals, and receives first signals which are sent by the real-time simulation system 5 and related to the working states of the power system and the high-voltage electrical accessory;
the real-time simulation system 5 is connected with a tested plug-in hybrid electric vehicle power system through a bus signal, the real-time simulation system 5 is connected with a half-shaft torque sensor 8 through a bus signal or a digital analog signal, the real-time simulation system 5 is connected with a loading motor 7 through a test system signal, and the real-time simulation system 5 sends a second signal related to parameter configuration of a rack.
Preferably, the first signal includes: the vehicle speed converted by the rotating speed of the loading motor 7, the rotating speed, the torque, the temperature and the oil consumption of the engine 17, the rotating speed, the torque, the direct current voltage, the direct current and the temperature of the driving motor 18, the temperature of the motor controller 2, the bus voltage, the bus current and the SOC of the power battery pack 15, the wheel speed, the master cylinder pressure, the wheel cylinder pressure and the pedal force of the hydraulic control unit 6, the input end voltage, the input current, the output end voltage and the output current of the DC/DC converter 13, the input end voltage, the input current, the output end voltage and the output current of the vehicle-mounted charger 16, the input end voltage and the input current of the electric air conditioning system simulation load 14, and the input end voltage and the input current of the PTC electric. The second signal includes: the key door, the opening degree of an accelerator pedal, the opening degree of a brake pedal, a gear switch and a mode switch operated by a driver, the working state of the electric air conditioning system simulation load 14 and the working state of the PTC electric heating system simulation load 12.
Preferably, the real-time simulation system 5 is loaded with a test cycle condition and a driver model related to the vehicle speed of the whole vehicle converted according to the rotating speed of the loading motor 7, and the test cycle condition is specifically represented by the formula (1):
k_Pedal＝kp*(CYC_Velocity_kmh-RealTime_Velocity_kmh) (1)
wherein k _ Pedal is the accelerator Pedal opening or the brake Pedal opening output by the driver model, kp is an adjustment coefficient, CYC _ Velocity _ kmh is a test cycle condition speed history, and RealTime _ Velocity _ kmh is the vehicle speed converted according to the rotating speed of the loading motor 7.
Preferably, the electric air conditioning system dummy load 14 and the PTC electric heating system dummy load 12 are programmable electronic loads.
Preferably, the operating resistances of the electric air conditioning system dummy load 14 and the PTC electrical heating system dummy load 12 are predicted from energy consumption data based on real vehicle test data.
Preferably, the prediction model applies a machine learning method to test the operating condition required power P, the ambient temperature T, and the temperature T of the power battery pack 15batSOC and temperature T of engine 17engTemperature T of the drive motor 18motTemperature T of motor controller 2ctlAs machine learning input, i.e. given an input sequence X ═ P, Tbat,SOC,Teng,Tmot,Tctl,]；
The output power P of the electric air conditioning system simulation load 14 and the PTC electric heating system simulation load 12 is usedHVACAnd PPTCAs machine learning output, i.e. Y ═ PHVAC,PPTC]；
According to the following steps (i) to (v), namely the formulas (2) to (6), the power P is output to the electric air-conditioning system simulation load 14 and the PTC electric heating system simulation load 12HVACAnd PPTCAnd (4) learning:
given that n learning feature maps are provided in the network, each feature map comprises k feature nodes, Z is usediRepresenting the ith feature map, i.e.
In the formula, WikRepresents the connection weight, beta, of the kth feature node in the ith set of mapping features to all inputsikAre correspondingly biased.
② all feature mappings in the feature node level can be expressed as
Let there be m enhanced nodes in the network and l enhanced nodes in the jth set of feature map, then H can be obtained in the same wayjI.e. by
In the formula, WjlRandom weight, β, representing the l-th enhanced node in the jth set of mapping featuresjlAre correspondingly biased.
Fourthly, all the feature maps in the enhanced node layer can be expressed as
Fifthly, the relationship between the network output and the network obtained by learning is
Y＝[Zn|Hm]Wm (6)
A system for testing power consumption of a plug-in hybrid vehicle powertrain, the system configured to execute on a plug-in hybrid vehicle powertrain power consumption test rack comprising:
the system comprises a vehicle control unit 1, a motor controller 2, a power assembly 4, a hydraulic control unit 6, a hydraulic brake 9, a differential mechanism 10, a low-voltage storage battery 11, a PTC electric heating system analog load 12, a DC/DC converter 13, an electric air conditioning system analog load 14, a power battery pack 15 and a vehicle-mounted charger 16;
wherein, the power assembly 4 and the differential mechanism 10, the differential mechanism 10 and the loading motor 7 are mechanically connected by adopting a shaft type; the power assembly 4 is electrically connected with the motor controller 2, the motor controller 2 is electrically connected with the power battery pack 15, and the power battery pack 15 is electrically connected with the DC/DC converter 13, the PTC electric heating system analog load 12, the electric air conditioning system analog load 14 and the vehicle-mounted charger 16 in a high voltage manner; the DC \ DC converter 13 is electrically connected with the low-voltage storage battery 11 by adopting low voltage;
the vehicle control unit 1, the motor controller 2, the power assembly 4, the hydraulic control unit 6, the power battery pack 15, the PTC electric heating system analog load 12, the electric air conditioning system analog load 14 and the vehicle-mounted charger 16 are connected by a CAN communication bus; the hydraulic control unit 6 and the hydraulic brake 9 are hydraulically connected.
Preferably, the power assembly 4 is structured such that the engine 17 is mechanically connected with the clutch 19, the driving motor 18 and the clutch 19 are together mechanically connected with the power coupling device 20, and the power coupling device 20 is mechanically connected with the transmission 21;
or the power assembly 4 is structurally characterized in that the engine 17 and the driving motor 18 are mechanically connected with the power coupling device 20 together, and the power coupling device 20 is mechanically connected with the speed changer 21;
or the power assembly 4 is structurally characterized in that the engine 17 is mechanically connected with the clutch 19, the clutch 19 is mechanically connected with the speed changer 21, and the driving motor 18 and the speed changer 21 are jointly mechanically connected with the power coupling device 20.
A plug-in hybrid vehicle powertrain energy consumption testing method performed in accordance with the plug-in hybrid vehicle powertrain energy consumption test bench, comprising:
step one, setting a loading test cycle working condition, and loading the test cycle working condition in a real-time simulation system 5;
step two, setting running resistance and setting a resistance coefficient in a loading motor 7;
setting working conditions of the high-voltage electrical accessory, wherein the working conditions are as follows: the electric air conditioning system works and the electric heating system works; and a second condition: the electric air conditioning system does not work, and the electric heating system works; and (3) carrying out a third condition: the electric air conditioning system works, and the electric heating system does not work; and a fourth condition: the electric air conditioning system does not work, and the electric heating system does not work;
step four, setting the initial state of the power battery pack 15, wherein the state I is as follows: the power battery pack 15 is at the highest state of charge at which charging is terminated; and a second state: the power battery pack 15 is in the lowest state of charge at the end of the operational discharge;
step five, preprocessing a rack, namely preprocessing the rack of the hybrid electric vehicle provided with the compression ignition engine by adopting a cycle specified by an accessory CA in appendix C in GB 18352.6-2016, and then completing the complete charging of the energy storage device according to the specification in appendix A;
step six, testing the circulating working condition, and normally operating the rack;
step seven, performing test post-treatment, and calculating the fuel consumption c1(L) by using a carbon balance method according to the calculation method of GB/T19233-2008 by utilizing the measured discharge amounts of CO2, CO and HC; charging the power battery pack 15 within 30min after the test is finished, measuring and recording electric energy e obtained from the power grid1(Wh)，e1Namely the electric energy consumption of the vehicle in the state under the condition;
if the initial state of the power battery pack 15 is less than 2, the fifth step to the seventh step are circulated, and the initial state of the power battery pack 15 is the current state plus 1;
if the working condition of the high-voltage electric accessory is less than 4, the fourth step to the seventh step are circulated, and the working condition of the high-voltage electric accessory is that 1 is added to the current condition;
and if the working condition of the high-voltage electric accessory is not less than 4, ending the test.
Preferably, the control mode of the power battery pack 15 in the initial state, the state one to the state two is that the power battery pack 15 operates to discharge, and the power battery pack operates on the test bed according to the following requirements until the discharge termination condition is met: the speed is stabilized at 50km/h +/-2 km/h until the engine of the hybrid electric vehicle is started by itself; if the engine is not started, the simulated vehicle cannot reach the stable speed of 50km/h +/-2 km/h, the vehicle speed is reduced to be suitable for ensuring the stable running of the vehicle, and the engine is not started within a specified time.
Compared with the prior art, the embodiment of the invention has the following specific beneficial effects:
the invention provides a rack and a test scheme which can test and verify the economic performance of the whole vehicle at the initial stage of design, research and development aiming at the energy consumption test of a power system of a plug-in hybrid electric vehicle, has a universal design for carrying various power assembly structural modes, covers the energy consumption analysis of an electric air conditioner and a PTC electric heating system, can load various actual or various circulating test working conditions, and provides a feasible and effective support for the economic performance evaluation based on actual traffic conditions and electric accessory use conditions at the initial stage of research and development of the whole vehicle.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a power consumption test bench and system for a plug-in hybrid vehicle powertrain;
FIG. 2 is a first power assembly structure of a power system energy consumption testing bench of a plug-in hybrid electric vehicle;
FIG. 3 is a second power assembly structure of a power system energy consumption test bench of the plug-in hybrid electric vehicle;
FIG. 4 is a third power assembly structure of a power system energy consumption test bench of a plug-in hybrid electric vehicle;
FIG. 5 is a bench test method for power consumption of a plug-in hybrid vehicle powertrain.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
FIG. 1 shows a plug-in hybrid vehicle powertrain energy consumption test bench, comprising:
the energy consumption testing bench for the power system of the plug-in hybrid electric vehicle comprises an upper computer 3, a real-time simulation system 5, a loading motor 7 and a half-shaft torque sensor 8, and is connected with a tested system through testing system signals such as digital quantity, analog quantity and CAN bus communication.
The upper computer 3 is responsible for parameter configuration and display of the test bench, is connected with the real-time simulation system 5 through test system signals, and receives first signals sent by the real-time simulation system 5 and related to the operating states of the power system and the high-voltage electrical accessory, wherein the first signals sent by the real-time simulation system 5 include but are not limited to: the vehicle speed converted by the rotating speed of the loading motor 7, the rotating speed, the torque, the temperature and the oil consumption of the engine 17, the rotating speed, the torque, the direct current, the controller temperature and the body temperature of the driving motor 18, the bus voltage, the bus current and the SOC of the power battery pack 15, the wheel speed, the master cylinder pressure, the wheel cylinder pressure and the pedal force of the hydraulic control unit 6, the input end voltage, the input current, the output end voltage and the output current of the DC/DC converter 13, the input end voltage, the input current, the output end voltage and the output current of the vehicle-mounted charger 16, the input end voltage and the input current of the electric air conditioning system simulation load 14, and the input end voltage and the input current of the PTC electric heating system simulation load 12.
The key door switch is used for turning on or off low-voltage direct-current electric equipment of the plug-in hybrid electric vehicle to be tested.
The real-time simulation system 5 is connected with the hybrid power system to be tested and other sensors through test system signals. The real-time simulation system 5 is connected with the tested plug-in hybrid electric vehicle power system through bus signals, and receives first signals related to the working states of the power system and the high-voltage electric accessories from the tested vehicle power system, the half-shaft torque sensor 8 and the loading motor 7, wherein the received signals include but are not limited to: the vehicle speed converted by the rotating speed of the loading motor 7, the rotating speed, the torque, the temperature and the oil consumption of the engine 17, the rotating speed, the torque, the direct current voltage, the direct current and the temperature of the driving motor 18, the temperature of the motor controller 2, the bus voltage, the bus current and the SOC of the power battery pack 15, the wheel speed, the master cylinder pressure, the wheel cylinder pressure and the pedal force of the hydraulic control unit 6, the input end voltage, the input current, the output end voltage and the output current of the DC/DC converter 13, the input end voltage, the input current, the output end voltage and the output current of the vehicle-mounted charger 16, the input end voltage and the input current of the electric air conditioning system simulation load 14, and the input end voltage and the input current of the PTC electric.
The real-time simulation system 5 sends a second signal related to the configuration of the rack parameters to the vehicle control unit 1, the PTC electrical heating system analog load 12, and the electric air conditioning system analog load 14, where the sending signals include, but are not limited to: and signals such as a key door operated by a driver, an opening degree of an accelerator pedal, an opening degree of a brake pedal, a gear switch and a mode switch, the working state of the electric air conditioning system simulation load 14, the working state of the PTC electric heating system simulation load 12 and the like are sent. The real-time simulation system 5 is connected with the half-shaft torque sensor 8 through a bus signal or a digital analog signal, and the received signal is the half-shaft torque. The real-time simulation system 5 is loaded with a test cycle working condition and a driver model related to the speed of the whole vehicle converted according to the rotating speed of the loading motor 7, and is specifically represented by the formula (1):
k_Pedal＝kp*(CYC_Velocity_kmh-RealTime_Velocity_kmh) (1)
wherein k _ Pedal is the accelerator Pedal opening or the brake Pedal opening output by the driver model, kp is an adjustment coefficient, CYC _ Velocity _ kmh is a test cycle condition speed history, and RealTime _ Velocity _ kmh is the vehicle speed converted according to the rotating speed of the loading motor 7.
The loading motor 7 simulates the road surface resistance of the vehicle, and the resistance curve is fitted by combining the energy consumption test related recommendation standard according to the set-up quality.
The electric air conditioning system simulation load 14 and the PTC electric heating system simulation load 12 are mainly composed of programmable electronic loads, in order to reflect the energy consumption of the electric air conditioning system and the PTC electric heating system under the real working condition, the working resistance value is predicted by energy consumption data based on real vehicle test data, and a machine learning method is applied to a prediction model to test the required power P of the working condition, the ambient temperature T and the temperature T of the power battery pack 15batSOC and temperature T of engine 17engTemperature T of the drive motor 18motTemperature T of motor controller 2ctlAs machine learning input, i.e. given an input sequence X ═ P, Tbat,SOC,Teng,Tmot,Tctl,](ii) a The output power P of the electric air conditioning system simulation load 14 and the PTC electric heating system simulation load 12 is usedHVACAnd PPTCAs machine learning output, i.e. Y ═ PHVAC,PPTC]；
According to the following steps from (1) to (6), the power P is output to the electric air-conditioning system analog load (14) and the PTC electric heating system analog load (12)HVACAnd PPTCAnd (4) learning:
given that n learning feature maps are provided in the network, each feature map comprises k feature nodes, Z is usediRepresenting the ith feature map, i.e.
In the formula, WikRepresents the connection weight, beta, of the kth feature node in the ith set of mapping features to all inputsikAre correspondingly biased.
② all feature mappings in the feature node level can be expressed as
Let there be m enhanced nodes in the network and l enhanced nodes in the jth set of feature map, then H can be obtained in the same wayjI.e. by
In the formula, WjlRandom weight, β, representing the l-th enhanced node in the jth set of mapping featuresjlAre correspondingly biased.
Fourthly, all the feature maps in the enhanced node layer can be expressed as
Fifthly, the relationship between the network output and the network obtained by learning is
Y＝[Zn|Hm]Wm (6)
The system for testing the energy consumption of the power system of the plug-in hybrid electric vehicle comprises a vehicle control unit 1, a motor controller 2, a power assembly 4, a hydraulic control unit 6, a hydraulic brake 9, a differential mechanism 10, a low-voltage storage battery 11, a PTC electric heating system analog load 12, a DC/DC converter 13, an electric air conditioning system analog load 14, a power battery pack 15 and a vehicle-mounted charger 16. Wherein, each part is unanimous with vehicle machinery electrical arrangement structure, specifically is: the power assembly 4 is mechanically connected with the differential mechanism 10, the differential mechanism 10 is mechanically connected with the loading motor 7 by adopting a shaft type; the power assembly 4 is electrically connected with the motor controller 2, the motor controller 2 is electrically connected with the power battery pack 15, and the power battery pack 15 is electrically connected with the DC/DC converter 13, the PTC electric heating system analog load 12, the electric air conditioning system analog load 14 and the vehicle-mounted charger 16 in a high voltage manner; the DC \ DC converter 13 is electrically connected with the low-voltage storage battery 11 by adopting low voltage; the vehicle control unit 1, the motor controller 2, the power assembly 4, the hydraulic control unit 6, the power battery pack 15, the PTC electric heating system analog load 12, the electric air conditioning system analog load 14 and the vehicle-mounted charger 16 are connected by a CAN communication bus; the hydraulic control unit 6 and the hydraulic brake 9 are hydraulically connected. The powertrain 4 may be configured in various forms, including, but not limited to, an engine 17, a driving motor 18, a clutch 19, a power coupling device 20, and a transmission 21.
Fig. 2 shows a first structure of the powertrain 4, in which the engine 17 is mechanically connected to the clutch 19, the driving motor 18 and the clutch 19 are together mechanically connected to the power coupling device 20, and the power coupling device 20 is mechanically connected to the transmission 21.
Fig. 3 shows a second structure of the powertrain 4, in which the engine 17 and the driving motor 18 are mechanically connected to the power coupling device 20, and the power coupling device 20 is mechanically connected to the transmission 21.
Fig. 4 shows a third structure of the powertrain 4, in which the engine 17 is mechanically connected to the clutch 19, the clutch 19 is mechanically connected to the transmission 21, and the driving motor 18 and the transmission 21 are mechanically connected to the power coupling device 20.
Fig. 5 is a power consumption bench test method for a plug-in hybrid vehicle power system, specifically:
step one, setting a loading test cycle working condition, and loading the test cycle working condition in the real-time simulation system 5.
Step two, setting the running resistance and setting the resistance coefficient in the loading motor 7.
Setting working conditions of the high-voltage electrical accessory, wherein the working conditions are as follows: the electric air conditioning system works and the electric heating system works; and a second condition: the electric air conditioning system does not work, and the electric heating system works; and (3) carrying out a third condition: the electric air conditioning system works, and the electric heating system does not work; and a fourth condition: the electric air conditioning system does not work, and the electric heating system does not work.
Step four, setting the initial state of the power battery pack 15, wherein the state I is as follows: the power battery pack 15 is at the highest state of charge at which charging is terminated; and a second state: the power battery pack 15 is at the lowest state of charge at the end of the operational discharge. The control mode from the first state to the second state is that the power battery pack 15 operates to discharge, and the power battery pack operates on the test bed according to the following requirements until the discharge termination condition is met: the speed is stabilized at 50km/h +/-2 km/h until the engine of the hybrid electric vehicle is started by itself; if the engine is not started, the simulated vehicle can not reach the stable speed of 50km/h +/-2 km/h, the speed is reduced to the proper speed for ensuring the stable running of the vehicle, and the engine is not started within the specified time; the engine should be shut down within 10s after the autostart, as recommended by the manufacturer.
And step five, preprocessing a rack, namely preprocessing the rack of the hybrid electric vehicle provided with the compression ignition engine by adopting a cycle specified by an accessory CA in appendix C in GB 18352.6-2016, and then completing the complete charging of the energy storage device according to the specification in appendix A.
And step six, testing the working condition circularly, and enabling the rack to normally operate.
And seventhly, performing test post-treatment, and calculating the fuel consumption c1(L) by using a carbon balance method according to the calculation method of GB/T19233-2008 by utilizing the measured emission amounts of CO2, CO and HC. And charging the power battery pack 15 within 30min after the test is finished, and measuring and recording the electric energy e1(Wh) obtained from the power grid, wherein e1 is the electric energy consumption of the vehicle in the state under the condition.
If the initial state of the power battery pack 15 is less than 2, the fifth step to the seventh step are circulated, and the initial state of the power battery pack 15 is the current state plus 1.
If the working condition of the high-voltage electric accessory is less than 4, the fourth step to the seventh step are circulated, and the working condition of the high-voltage electric accessory is that the current condition is added with 1.
And if the working condition of the high-voltage electric accessory is not less than 4, ending the test.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present invention.
Claims (10)
1. A plug-in hybrid vehicle driving system energy consumption test bench, comprising: the system comprises an upper computer (3), a real-time simulation system (5), a loading motor (7) and a half-shaft torque sensor (8);
the upper computer (3) is used for configuring and displaying parameters of the test bench, is connected with the real-time simulation system (5) through test system signals, and receives first signals which are sent by the real-time simulation system (5) and related to the working states of the power system and the high-voltage electrical accessory;
the real-time simulation system (5) is connected with a tested plug-in hybrid electric vehicle power system through a bus signal, the real-time simulation system (5) is connected with the half-shaft torque sensor (8) through a bus signal or a digital analog signal, the real-time simulation system (5) is connected with the loading motor (7) through a test system signal, and the real-time simulation system (5) sends a second signal related to the configuration of the parameters of the rack.
2. The plug-in hybrid vehicle powertrain system energy consumption test bench of claim 1, wherein the first signal comprises: the method comprises the steps of loading the whole vehicle speed converted by the rotating speed of a motor (7), the rotating speed, the torque, the temperature and the oil consumption of an engine (17), the rotating speed, the torque, the direct current voltage, the direct current and the temperature of a driving motor (18), the temperature of a motor controller (2), the bus voltage, the bus current and the SOC of a power battery pack (15), the wheel speed, the master cylinder pressure, the wheel cylinder pressure and the pedal force of a hydraulic control unit (6), the input end voltage, the input current, the output end voltage and the output current of a DC/DC converter (13), the input end voltage, the input current, the output end voltage and the output current of a vehicle-mounted charger (16), the input end voltage and the input current of an electric air conditioning system analog load (14), and the input end voltage and the input current of a PTC electric heating system analog; the second signal includes: the device comprises a key door operated by a driver, an accelerator pedal opening degree, a brake pedal opening degree, a gear switch and a mode switch, wherein the electric air-conditioning system simulates the working state of a load (14), and the PTC electric heating system simulates the working state of a load (12).
3. The plug-in hybrid vehicle powertrain energy consumption test bench of claim 2, wherein the real-time simulation system (5) is loaded with a test cycle condition and a driver model related to the vehicle speed of the entire vehicle converted according to the rotation speed of the loading motor (7), and the test cycle condition is specifically represented by the following formula (1):
k_Pedal＝kp*(CYC_Velocity_kmh-RealTime_Velocity_kmh) (1)
the method comprises the steps that k _ Peal is the opening degree of an accelerator Pedal or the opening degree of a brake Pedal output by a driver model, kp is an adjusting coefficient, CYC _ Velocity _ kmh is a speed process of a test cycle working condition, and RealTime _ Velocity _ kmh is the speed of the whole vehicle converted according to the rotating speed of a loading motor (7).
4. The plug-in hybrid vehicle powertrain system energy consumption test bench of claim 2, characterized in that the electric air conditioning system dummy load (14) and the PTC electric heating system dummy load (12) are programmable electronic loads.
5. The plug-in hybrid vehicle powertrain system energy consumption test bench of claim 4, characterized in that the operating resistance values of the electric air conditioning system dummy load (14) and the PTC electric heating system dummy load (12) are predicted from energy consumption data based on real vehicle test data.
6. The plug-in hybrid vehicle powertrain system energy consumption test bench of claim 5, characterized in that the predictive model applies a machine learning method to test the operating condition demand power P, the ambient temperature T, the temperature T of the power battery pack (15)batSOC and temperature T of engine (17)engTemperature T of the drive motor (18)motTemperature T of motor controller 2ctlAs machine learning input, i.e. given an input sequence X ═ P, Tbat,SOC,Teng,Tmot,Tctl,]；
The output power P of the electric air conditioning system simulation load (14) and the PTC electric heating system simulation load (12)HVACAnd PPTCAs machine learning output, i.e. Y ═ PHVAC,PPTC]；
According to the following steps from (1) to (6), the power P is output to the electric air-conditioning system analog load (14) and the PTC electric heating system analog load (12)HVACAnd PPTCAnd (4) learning:
given that n learning feature maps are provided in the network, each feature map comprises k feature nodes, Z is usediRepresenting the ith feature map, i.e.
In the formula, WikRepresents the connection weight, beta, of the kth feature node in the ith set of mapping features to all inputsikAre correspondingly biased.
② all feature mappings in the feature node level can be expressed as
Let there be m enhanced nodes in the network and l enhanced nodes in the jth set of feature map, then H can be obtained in the same wayjI.e. by
In the formula, WjlRandom weight, β, representing the l-th enhanced node in the jth set of mapping featuresjlAre correspondingly biased.
Fourthly, all the feature maps in the enhanced node layer can be expressed as
Fifthly, the relationship between the network output and the network obtained by learning is
Y＝[Zn|Hm]Wm (6)
7. A plug-in hybrid vehicle powertrain energy consumption testing system implemented based on the plug-in hybrid vehicle powertrain energy consumption test rack of claims 1-6, comprising:
the system comprises a vehicle control unit (1), a motor controller (2), a power assembly (4), a hydraulic control unit (6), a hydraulic brake (9), a differential (10), a low-voltage storage battery (11), a PTC electric heating system analog load (12), a DC/DC converter (13), an electric air conditioning system analog load (14), a power battery pack (15) and a vehicle-mounted charger (16);
wherein, the power assembly (4) is mechanically connected with the differential (10) and the differential (10) is mechanically connected with the loading motor (7) by a shaft; the power assembly (4) is electrically connected with the motor controller (2), the motor controller (2) is electrically connected with the power battery pack (15), and the power battery pack (15) is electrically connected with the DC \ DC converter (13), the PTC electric heating system analog load (12), the electric air conditioning system analog load (14) and the vehicle-mounted charger (16) by adopting high voltage; the DC \ DC converter (13) is electrically connected with the low-voltage storage battery (11) by adopting low voltage;
the vehicle-mounted electric air conditioning system comprises a vehicle control unit (1), a motor controller (2), a power assembly (4), a hydraulic control unit (6), a power battery pack (15), a PTC electric heating system analog load (12), an electric air conditioning system analog load (14) and a vehicle-mounted charger (16), which are connected by a CAN communication bus; the hydraulic control unit (6) and the hydraulic brake (9) are connected hydraulically.
8. The plug-in hybrid vehicle powertrain system energy consumption testing system of claim 7, wherein:
the power assembly (4) is structurally characterized in that an engine (17) is mechanically connected with a clutch (19), a driving motor (18) and the clutch (19) are mechanically connected with a power coupling device (20) together, and the power coupling device (20) is mechanically connected with a transmission (21);
or the power assembly (4) is structurally characterized in that an engine (17) and a driving motor (18) are mechanically connected with a power coupling device (20) together, and the power coupling device (20) is mechanically connected with a speed changer (21);
or the power assembly (4) is structurally characterized in that the engine (17) is mechanically connected with the clutch (19), the clutch (19) is mechanically connected with the speed changer (21), and the driving motor (18) and the speed changer (21) are together mechanically connected with the power coupling device (20).
9. A plug-in hybrid vehicle powertrain energy consumption testing method performed according to one of claims 1-6 on a plug-in hybrid vehicle powertrain energy consumption test bench, comprising:
step one, setting a loading test cycle working condition, and loading the test cycle working condition in a real-time simulation system (5);
step two, setting running resistance and setting a resistance coefficient in a loading motor (7);
setting working conditions of the high-voltage electrical accessory, wherein the working conditions are as follows: the electric air conditioning system works and the electric heating system works; and a second condition: the electric air conditioning system does not work, and the electric heating system works; and (3) carrying out a third condition: the electric air conditioning system works, and the electric heating system does not work; and a fourth condition: the electric air conditioning system does not work, and the electric heating system does not work;
step four, setting the initial state of the power battery pack (15), wherein the state I is as follows: the power battery pack (15) is in the highest charge state of charge of the charging termination; and a second state: the power battery pack (15) is in the lowest charge state at the end of running discharge;
step five, preprocessing a rack, namely preprocessing the rack of the hybrid electric vehicle provided with the compression ignition engine by adopting a cycle specified by an accessory CA in appendix C in GB 18352.6-2016, and then completing the complete charging of the energy storage device according to the specification in appendix A;
step six, testing the circulating working condition, and normally operating the rack;
step seven, performing test post-treatment, and calculating the fuel consumption c1(L) by using a carbon balance method according to the calculation method of GB/T19233-2008 by utilizing the measured discharge amounts of CO2, CO and HC; charging the power battery pack (15) within 30min after the test is finished, measuring and recording electric energy e obtained from the power grid1(Wh)，e1Namely the electric energy consumption of the vehicle in the state under the condition;
if the initial state of the power battery pack (15) is less than 2, the fifth step to the seventh step are circulated, and the initial state of the power battery pack (15) is the current state plus 1;
if the working condition of the high-voltage electric accessory is less than 4, the fourth step to the seventh step are circulated, and the working condition of the high-voltage electric accessory is that 1 is added to the current condition;
and if the working condition of the high-voltage electric accessory is not less than 4, ending the test.
10. The plug-in hybrid vehicle powertrain energy consumption testing method of claim 9, wherein: the control mode from the initial state of the power battery pack (15) to the first state is that the power battery pack (15) is discharged when running, and the power battery pack runs on a test bench according to the following requirements until the discharge termination condition is met: the speed is stabilized at 50km/h +/-2 km/h until the engine of the hybrid electric vehicle is started by itself; if the engine is not started, the simulated vehicle cannot reach the stable speed of 50km/h +/-2 km/h, the vehicle speed is reduced to be suitable for ensuring the stable running of the vehicle, and the engine is not started within a specified time.
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