CN111332274A - Optimal method for calibration parameters of hybrid power bus controller - Google Patents

Optimal method for calibration parameters of hybrid power bus controller Download PDF

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CN111332274A
CN111332274A CN202010180158.7A CN202010180158A CN111332274A CN 111332274 A CN111332274 A CN 111332274A CN 202010180158 A CN202010180158 A CN 202010180158A CN 111332274 A CN111332274 A CN 111332274A
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CN111332274B (en
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宋大凤
杨丽丽
云千芮
曾小华
梁伟智
王诗元
郑琦
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Jilin University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W20/00—Control systems specially adapted for hybrid vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W20/00—Control systems specially adapted for hybrid vehicles
    • B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
    • B60W20/15—Control strategies specially adapted for achieving a particular effect
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces

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Abstract

The invention discloses a method for optimizing calibration parameters of a whole vehicle controller of a hybrid power bus, and relates to the technical field of hybrid power vehicles. The method mainly comprises five steps of selecting a whole vehicle constraint boundary and a calibration response, calculating hundred kilometers of theoretical oil consumption based on average comprehensive energy transfer efficiency, making a whole vehicle energy management strategy based on engine optimal control, constructing optimal calibration parameters according to the energy management strategy, and determining a one-dimensional calibration parameter feasible region. The method is favorable for quickly optimizing the calibration parameters of the whole vehicle controller of the hybrid power bus, reduces the range of the feasible calibration parameters and shortens the research and development period of the whole vehicle controller.

Description

Optimal method for calibration parameters of hybrid power bus controller
Technical Field
The invention belongs to the technical field of hybrid electric vehicles, and particularly relates to a method for optimizing calibration parameters of a whole hybrid electric vehicle controller.
Background
The passenger car is an important vehicle and plays an important role in both our living and national economic development. With the continuous reduction of fossil energy, the conventional passenger car is gradually changed to a new energy passenger car, and the hybrid power passenger car is used as an important component of the new energy passenger car, so that the dynamic property of the whole passenger car is ensured, the energy conservation and the emission reduction are realized, and the hybrid power passenger car has a good application prospect. Compared with the conventional passenger car, the whole vehicle controller of the hybrid power passenger car is much more complex, because the hybrid power passenger car has multiple working modes, how to control the switching of the various working modes and the distribution of system torque are the working core of the whole vehicle controller of the hybrid power passenger car. Usually, a calibration process is needed when a vehicle controller is designed, and a calibration result directly influences the control effect of the vehicle controller, most researches usually select the optimal calibration parameter and the feasible region thereof through continuous tests, but the process is complicated and low in efficiency, and the development period of the controller is prolonged.
The Chinese patent publication No. CN 108515962A, the publication No. 2018-09-11, discloses a method for rapidly calibrating a whole vehicle controller of a hybrid electric vehicle, and the method mentions that on the premise of meeting the whole vehicle dynamic property, one-dimensional calibration parameters are extracted by taking fuel economy and electric energy consumption as calibration targets and a feasible region is determined, so that the calibration process is more ordered, the calibration efficiency is improved, but in the method, a plurality of charge state tests are required to obtain the fuel consumption and the electric energy consumption, no specific fuel consumption function is provided for facilitating simulation, and the method does not consider the influence of SOC imbalance on the calibration response; secondly, the method does not analyze the energy management strategy based on the rules layer by layer, so that the number of the selected calibration parameters is large, and the action of theoretical analysis and actual experience is not considered, so that the feasible region interval of the calibration parameters is too large, and the calibration work is not facilitated.
The optimal selection method for the calibration parameters of the whole vehicle controller of the hybrid power bus, provided by the invention, has the advantages that the theoretical oil consumption based on the average comprehensive energy transfer efficiency is deduced to be used as the calibration response, the whole vehicle energy management strategy based on the optimal control of the engine is deeply analyzed, the calibration parameters closely related to the economy of the whole vehicle are preferably selected, and the calibration parameters are determined in a smaller feasible region interval by a method combining theoretical analysis and experience, so that the selection of the calibration parameters and the determination of the feasible region are favorably and rapidly carried out.
Disclosure of Invention
The invention provides a method for optimizing the calibration parameters of the whole vehicle controller of a hybrid power bus, aiming at solving the problems that the optimization process of the calibration parameters of the whole vehicle controller of the hybrid power bus is complicated and the feasible range of the calibration parameters is large at present, and aiming at giving full play to the fuel-saving performance of the hybrid power bus, the optimization of the calibration parameters of the whole vehicle controller is carried out around the economy of the whole vehicle, the calibration parameters of the whole vehicle controller can be selected quickly, and the research and development period of the whole vehicle controller is shortened.
In order to achieve the above object, a preferred method for calibrating parameters of a hybrid electric vehicle controller according to an embodiment of the present invention includes the following steps:
the method comprises the following steps of firstly, selecting a finished automobile constraint boundary and a calibration response, and specifically comprising the following steps:
①, taking the dynamic property of the hybrid electric bus as a whole vehicle constraint boundary;
②, taking hundred kilometers of theoretical oil consumption meeting the electric quantity balance condition as a calibration response;
and step two, deducing a hundred kilometer theoretical oil consumption formula obtained by average comprehensive energy transfer efficiency, and specifically comprising the following steps of:
① the hybrid power system is divided into a power source module, a transmission system module and a vehicle body module, wherein the power source module comprises an engine and a motor, the transmission system module comprises a planetary gear mechanism, a gearbox and a main reducer, and the vehicle body module mainly refers to a longitudinal dynamic model of the whole vehicle;
② deriving an average combined energy transfer efficiency η for the hybrid powertrain from the energy transfer relationships between the power source modules, the driveline modules, and the body modulestrAs shown in formula (1):
Figure BDA0002412233900000021
in the formula, EiceIndicating the actual supply of energy to the engine, EdchgRepresents the total energy of discharge of the battery, EchgRepresenting the total energy charged in the battery, ErgbRepresenting regenerative braking energy transmitted from the wheels to the battery via the transmission system, EwhExpressing the theoretical driving total energy of the cycle condition at the wheel, wherein delta SOC expresses the SOC difference value of the battery at the beginning and the end of the cycle condition simulation;
defining the actual energy E supplied by the engineiceAs shown in formula (2):
Figure BDA0002412233900000022
in the formula (f)eRepresenting one hundred kilometers theoretical oil consumption, be,avgRepresenting the average fuel consumption of the engine, C representing the conversion coefficient of units of fuel consumption, MeIndicating the fuel injection quantity, P, of the engineeRepresenting engine power;
defining the theoretical total driving energy E of the cycle condition at the wheelwhAs shown in formula (3):
Figure BDA0002412233900000023
in the formula, Ft,D(t) represents the theoretical driving force demand of the cycle condition, and v (t) represents the theoretical vehicle speed of the cycle condition;
③, deriving a hundred kilometers theoretical oil consumption calculation formula based on the average integrated energy transmission efficiency defined above, as shown in formula (4):
Figure BDA0002412233900000031
calculating the equivalent of the charging and discharging electric quantity of the battery to the theoretical oil consumption of one hundred kilometers, finally obtaining the theoretical oil consumption of one hundred kilometers under the condition of electric quantity balance as shown in the formula (5), and taking the theoretical oil consumption of one hundred kilometers under the condition of electric quantity balance as a calibration response;
Figure BDA0002412233900000032
thirdly, a whole vehicle energy management strategy based on the optimal control of the engine is formulated, and the method specifically comprises the following steps:
①, determining the driver demand torque, wherein the driver demand torque is determined by the pedal opening and the current vehicle speed, solving the current pedal opening by using a PID controller according to the target vehicle speed and the actual vehicle speed, calculating the system maximum output torque under the current vehicle speed, and multiplying the current pedal opening, the system maximum output torque under the current vehicle speed and the torque correction coefficient under the current vehicle speed to obtain the driver demand torque;
②, making system working mode switching rules, including switching rules among motion states, switching rules among working modes and switching rules of sub-modes under each working mode;
③ distributing system torque according to the working state of each component in different working modes of the system;
fourthly, according to the optimized calibration parameters of the energy management strategy framework, the calibration parameters are selected and respectively used as the pedal opening torque correction coefficient function f according to the driver required torque, the system working mode switching rule and the system torque distribution under different working modes determined in the third stepξ(PS), mode switch SOC threshold value SOCoMode switching power threshold PoSOC lower limit value SOC for mode switching in EVT modepSOC upper limit value SOC for mode switching in EVT modeHLower limit value P of mode switching powerpSOC threshold margin lower limit value delta SOCtpSOC threshold margin upper limit value delta SOCthPower thresholdMargin of value Δ PtpCharging power PchgAnd a motor MG2 speed threshold n in the regenerative braking energy recovery modemoAnd the speed difference L of the lifting gear curve of the gearboxsv；
Fifthly, determining a feasible domain of the one-dimensional calibration parameters, which specifically comprises the following steps:
① determining the calibration parameter range related to battery characteristics, considering vehicle economy and preventing over discharge of battery, and further ensuring SOC according to the relation curve of battery internal resistance and SOCoThe feasible region is in the range with smaller internal resistance of the battery; considering the economy of the whole vehicle and the non-frequent switching of the working mode, determining the delta SOC according to the fact that the difference value of the initial and final variation of the SOC of the battery is within 2 percenttpAnd Δ SOCthThe feasible region interval of (1); according to Δ SOCtpAnd Δ SOCthCan calculate the SOCpAnd SOCHTo determine the SOCpAnd SOCHThe feasible region interval of (1);
② determining the calibration parameter feasible region related to the power threshold value, comprehensively considering the battery SOC balance and the pure electric mode as much as possible, and further ensuring P according to the required power-vehicle speed scatter diagramoThe feasible region interval comprises 50 to 80 percent of required power values; considering the economy of the whole vehicle and the frequent switching of the working mode, the reference delta SOCtpAnd SOCoSelecting the proportion and determining the delta PtpThe feasible region interval of (1); according to Δ PtpP can be calculatedpAnd further determine PpThe feasible region interval of (1);
③ determining charging power PchgConsidering the battery charging speed and the battery capacity, and determining P according to the charging power of the charging equipment externally connected with the vehiclechgThe feasible region interval of (1);
④ determining the threshold value n for the speed of the motor MG2 in the regenerative braking energy recovery modemoThe feasible region of the motor MG2 is considered, the working efficiency and the regenerative braking energy recovery rate of the motor MG2 are considered, and n is ensured according to the efficiency curve of the motormoThe feasible region is in the range of higher motor efficiency;
⑤ determining the curve speed difference L of the gear boxsvEmpirically, the downshift curve is shifted left by about L from the upshift curvesvIndividual unit, then estimate L according to a specific shift strategysvCan be performed in the domain interval.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the optimal selection method for the calibration parameters of the whole vehicle controller of the hybrid power bus, the hundred-kilometer theoretical oil consumption formula based on the average comprehensive energy transfer efficiency is deduced, the influence of SOC unbalance on calibration response is eliminated, the calibration response can be obtained through simulation analysis, and repeated tests are not needed;
2. the method for optimizing the calibration parameters of the whole vehicle controller of the hybrid power bus uses a whole vehicle energy management strategy based on the optimal control of an engine as a core algorithm of the whole vehicle controller, and performs calibration work based on the algorithm, so that the method has the advantages of simple design, quick response, good robustness and the like;
3. according to the method for optimizing the calibration parameters of the whole vehicle controller of the hybrid electric bus, the calibration parameters are determined in a smaller feasible region interval by a method combining theoretical analysis and experience, so that the method is beneficial to quickly optimizing the calibration parameters and the feasible region of the whole vehicle controller of the hybrid electric bus, and the research and development period of a product is shortened.
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The invention is further described with reference to the accompanying drawings in which:
FIG. 1 is a schematic diagram of a hybrid passenger vehicle system according to an embodiment of the present invention;
FIG. 2 is a general flow chart of a preferred method for calibrating parameters of a hybrid electric vehicle controller in the embodiment of the invention;
FIG. 3 is a hybrid passenger vehicle energy flow configuration in an embodiment of the present invention;
FIG. 4 is a block diagram of a hybrid powertrain hierarchy control architecture in an embodiment of the present invention;
FIG. 5 is a flow chart illustrating the rules for switching between electric-only mode and hybrid mode in an embodiment of the present invention;
FIG. 6 is a flow chart of the switching rules between the hybrid mode and the engine direct drive mode in an embodiment of the present invention;
Detailed Description
The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
The invention relates to a method for optimizing calibration parameters of a hybrid power bus controller, which specifically comprises the following steps:
referring to fig. 1, the hybrid electric vehicle in the embodiment adds two power sources, namely, an electric motor MG1 and an electric motor MG2, as well as a two-speed transmission (including a low speed gear and a high speed gear), a brake B1 and a planetary gear mechanism PG, compared with a conventional vehicle. The planetary gear mechanism PG is used as a power coupling device of the transmission system of the whole vehicle, the output shaft of the engine is connected with the planet carrier of the PG, and power is divided by the PG and is output at the gear ring; the motor MG1 is connected with the sun gear of the PG and has the function of adjusting the rotating speed of the engine; the motor MG2 is connected with the input shaft of the two-gear gearbox, and transmits power to a transmission shaft in front of the main speed reducer through the gearbox; the motor MG1 and the power battery pack are in electric connection through the MG1 controller and the high-voltage distribution box, and the motor MG2 and the power battery pack are in electric connection through the MG2 controller and the high-voltage distribution box; brake B1 may be used to lock the sun gear of planetary gear PG so that the system operates in different drive modes.
The hybrid power bus in the embodiment can realize a pure electric mode, a hybrid power mode, an engine direct drive mode, a mechanical braking mode and a regenerative braking energy recovery mode of the whole bus, and the two-gear gearbox can realize the switching of high and low gear positions in any mode, so that the working mode of the whole bus is further enriched. Because the planetary gear mechanism can realize double decoupling of the rotating speed, the torque and the road load of the engine, the planetary gear mechanism has an electronic stepless speed change function, the engine has wider working space, the optimal control of the engine is easy to realize, and good economy of the whole vehicle and working condition adaptability can be obtained.
Referring to the attached figure 2, the method provided by the invention mainly comprises five steps of selecting a finished automobile constraint boundary and a calibration response, calculating hundred kilometers of theoretical oil consumption based on average comprehensive energy transfer efficiency, making a finished automobile energy management strategy based on optimal control of an engine, constructing optimal calibration parameters according to the energy management strategy, and determining a one-dimensional calibration parameter feasible region.
The method comprises the following steps that firstly, the dynamic performance of the hybrid power bus is used as a whole bus constraint boundary, and the hundred kilometers of theoretical oil consumption under the condition of electric quantity balance is used as a calibration response.
The second step, referring to fig. 3, is to derive the theoretical oil consumption formula of hundred kilometers determined from the average integrated energy transfer efficiency, which specifically includes the following steps, wherein E in fig. 3fuelRepresenting total energy consumed by the engine, EiceIndicating the actual supply of energy to the engine, EdchgRepresents the total energy of discharge of the battery, EchgRepresenting the total energy charged in the battery, Edchg*Indicating total energy supplied by the motor, Echg*Representing the total energy transferred by the system to the motor, ErgbRepresenting regenerative braking energy transmitted from the wheels to the battery via the transmission system, EwhRepresenting the theoretical driving total energy of the cycle condition at the wheel;
① the hybrid power system is divided into a power source module, a transmission system module and a vehicle body module, wherein the power source module comprises an engine and a motor, the transmission system module comprises a planetary gear mechanism, a gearbox and a main reducer, and the vehicle body module mainly refers to a longitudinal dynamic model of the whole vehicle;
② deriving an average combined energy transfer efficiency η for the hybrid powertrain from the energy transfer relationships between the power source modules, the driveline modules, and the body modulestrAs shown in formula (1):
Figure BDA0002412233900000061
in the formula, delta SOC represents the SOC difference value of the battery at the beginning and the end of the cycle condition simulation;
defining the actual energy E supplied by the engineiceAs shown in formula (2):
Figure BDA0002412233900000062
in the formula (f)eRepresenting one hundred kilometers theoretical oil consumption, be,avgRepresenting the average fuel consumption of the engine, C representing the conversion coefficient of units of fuel consumption, MeIndicating the fuel injection quantity, P, of the engineeRepresenting engine power;
defining the theoretical total driving energy E of the cycle condition at the wheelwhAs shown in formula (3):
Figure BDA0002412233900000063
in the formula, Ft,D(t) represents the theoretical driving force demand of the cycle condition, and v (t) represents the theoretical vehicle speed of the cycle condition;
③, deriving a hundred kilometers theoretical oil consumption calculation formula based on the average integrated energy transmission efficiency defined above, as shown in formula (4):
Figure BDA0002412233900000071
and equivalently calculating the charge and discharge electric quantity of the battery to the theoretical oil consumption of one hundred kilometers, finally obtaining the theoretical oil consumption of one hundred kilometers under the condition of electric quantity balance as shown in the formula (5), and taking the theoretical oil consumption of one hundred kilometers under the condition of electric quantity balance as a calibration response.
Figure BDA0002412233900000072
Thirdly, referring to the attached figure 4, a whole vehicle energy management strategy based on the optimal control of the engine is formulated, the characteristic that a planetary gear mechanism has power splitting is utilized, the engine is controlled to work near an optimal working curve, and the insufficient or excessive part of the required torque of the whole vehicle is compensated by a motor MG2, so that the optimal control of the engine is realized, and the good economy of the whole vehicle is ensured; the method comprises the following steps that a whole vehicle energy management strategy framework based on the optimal control of an engine is divided into a management layer, a subsystem coordination layer and an execution subsystem layer, the management layer determines the opening degrees of an accelerator pedal and a brake pedal according to the current working condition and the driving intention, the subsystem coordination layer determines the current working mode based on pedal signals and feedback signals and distributes torque to components and sends control signals, and the execution subsystem layer controls the working states of the components such as the engine, a motor, a battery, an AMT (automated mechanical transmission), a brake and the like according to the control signals, and specifically comprises the following steps:
①, determining the driver demand torque, wherein the driver demand torque is determined by the pedal opening and the current vehicle speed, solving the current pedal opening by using a PID controller according to the target vehicle speed and the actual vehicle speed, calculating the system maximum output torque under the current vehicle speed, and multiplying the current pedal opening, the system maximum output torque under the current vehicle speed and the torque correction coefficient under the current vehicle speed to obtain the driver demand torque;
②, making system working mode switching rules, including switching rules among motion states, switching rules among working modes and switching rules of sub-modes under each working mode;
wherein, the switching rule among the motion states is shown in table 1:
TABLE 1 switching rules for motion states
Figure BDA0002412233900000073
(Note: PS)DIndicates an accelerator pedal opening degree; PS (polystyrene) with high sensitivityBIndicating the opening of the brake pedal
The switching rules among the working modes comprise a switching rule between a pure electric mode and a hybrid power mode, a switching rule between the hybrid power mode and an engine direct drive mode and a switching rule for switching a regenerative braking energy recovery mode to a mechanical braking mode, the pure electric mode and the engine direct drive mode cannot be directly switched, the pure electric mode and the engine direct drive mode can be switched to the corresponding modes only by passing through the hybrid power mode, and the specific content of each rule is as follows:
referring to FIG. 5, EV is shown for electric only mode, EVT is shown for hybrid mode, SOCoIndicates a mode switch SOC threshold value, PoIndicating a mode switching power threshold, SOCHIndicating mode cut in EVT modeUpper limit value of converted SOC, SOCpRepresents the lower SOC limit, P, for mode switching in EVT modepIndicating a lower limit of mode switching power, PrepRepresenting the required power; when the vehicle is switched from the pure electric mode to the hybrid power mode, comparing the current battery SOC with a mode switching SOC threshold value, if the current battery SOC is smaller than the mode switching SOC threshold value, switching the vehicle working die into the hybrid power mode, if the current battery SOC is larger than or equal to the mode switching SOC threshold value, comparing the required power with the mode switching power threshold value, if the required power is larger than the mode switching power threshold value, switching the vehicle working mode into the hybrid power mode, otherwise, still setting the vehicle working mode as the pure electric mode; when the vehicle is switched from the hybrid mode to the electric-only mode, the current SOC of the battery is compared with the lower limit value of the SOC of the mode switching in the EVT mode, if the current battery SOC is less than or equal to the SOC lower limit value for the mode switch in the EVT mode, the vehicle operation mode is still the hybrid mode, if the current battery SOC is larger than the SOC lower limit value of the mode switching in the EVT mode, the required power and the mode switching power lower limit value are compared, if the required power is less than the mode switching power lower limit value, the vehicle working mode is switched to a pure electric mode, if the required power is greater than or equal to the lower mode switching power limit, the current battery SOC is compared with the upper mode switching SOC limit in the EVT mode, if the current battery SOC is larger than the SOC upper limit value of the mode switching in the EVT mode, the vehicle working mode is switched to a pure electric mode, otherwise, the vehicle working mode is still a hybrid power mode;
referring to FIG. 6, ENG indicates engine direct drive mode, TreqIndicating the required torque, Te,maxIndicating the maximum output torque of the engine, PallRepresenting the total power demanded, Pe.maxThe maximum output power of the engine is represented, when the vehicle is switched from a hybrid power mode to a direct drive mode of the engine, the required power is compared with a mode switching power threshold value, if the required power is smaller than or equal to the mode switching power threshold value, the working mode of the vehicle is still in the hybrid power mode, and if the required power is larger than the mode switching power threshold valueWhen the vehicle is in the EVT mode, comparing the current battery SOC with the SOC upper limit value of mode switching in the EVT mode, if the current battery SOC is larger than the SOC upper limit value of mode switching in the EVT mode, switching the vehicle working mode to the engine direct drive mode, if the current battery SOC is smaller than or equal to the SOC upper limit value of mode switching in the EVT mode, comparing the required torque with the maximum output torque of the engine, if the required torque is smaller than the maximum output torque of the engine, switching the vehicle working mode to the engine direct drive mode, otherwise, still setting the vehicle working mode to be the hybrid power mode; when the vehicle is switched from the engine direct drive mode to the hybrid power mode, if the required power is less than or equal to a mode switching power threshold value, the vehicle working mode is still the hybrid power mode, if the required power is greater than the mode switching power threshold value, the required total power is compared with the maximum output power of the engine, if the required total power is greater than the maximum output power of the engine, the vehicle working mode is still the hybrid power mode, otherwise, the vehicle working mode is switched to the engine direct drive mode;
when the rotating speed of the motor MG2 is greater than the rotating speed critical value of the motor MG2 in the regenerative braking energy recovery mode, the working mode of the vehicle is still the regenerative braking energy recovery mode, otherwise, the working mode of the vehicle is switched to the mechanical braking mode;
the difference between the sub-modes in each working mode is that the gears of the gearbox are different, gear lifting is determined by the vehicle speed and the torque required by the gearbox, the torque required by the gearbox is determined by the external characteristic of the motor MG2, and the gear is translated leftwards by L according to a gear-up curvesvThe speed units determine the downshift profile.
③ distributing the system torque according to the working state of each component in different working modes of the system, the concrete distribution steps are as follows:
in the pure electric mode, the whole vehicle is powered by a power battery pack, and the torque of the whole vehicle is provided by a motor MG 2; in a hybrid power mode, the required torque of the whole vehicle is provided by the engine firstly, the insufficient torque is provided by the motor MG2, and the motor MG1 is required to regulate and control the engine to work near an optimal working curve; in the engine direct drive mode, the torque of the whole vehicle is provided by the engine; under the regenerative braking energy recovery mode, the torque of the whole vehicle is provided by the motor MG2, and when the braking demand torque is larger and exceeds the external characteristic of the motor MG2, the mechanical brake needs to provide extra braking torque to ensure the timely braking of the whole vehicle.
Fourthly, according to the optimized calibration parameters of the energy management strategy framework, the calibration parameters are selected and respectively used as the pedal opening torque correction coefficient function f according to the driver required torque, the system working mode switching rule and the system torque distribution under different working modes determined in the third stepξ(PS), mode switch SOC threshold value SOCoMode switching power threshold PoSOC lower limit value SOC for mode switching in EVT modepSOC upper limit value SOC for mode switching in EVT modeHLower limit value P of mode switching powerpSOC threshold margin lower limit value delta SOCtpSOC threshold margin upper limit value delta SOCthPower threshold margin Δ PtpCharging power PchgAnd a motor MG2 speed threshold n in the regenerative braking energy recovery modemoAnd the speed difference L of the lifting gear curve of the gearboxsv。
Fifthly, determining a feasible domain of the one-dimensional calibration parameters, which specifically comprises the following steps:
① determine the feasible region of calibration parameters related to battery characteristics, and based on experience, SOCoSmall value, over-discharge of the battery, SOCoThe value is large, the economy of the whole vehicle is deteriorated, and the SOC is ensured according to the relation curve of the internal resistance of the battery and the SOCoThe value is taken in the range of smaller internal resistance of the battery, and the SOC is determined according to the theory and the experienceoThe feasible region interval of (1); empirically,. DELTA.SOCtpAnd Δ SOCthWith small values, the vehicle will frequently switch between EV and EVT modes, Δ SOCtpAnd Δ SOCthThe value is large, the economy of the whole vehicle is deteriorated, and the delta SOC is further determined according to the fact that the difference value of the initial and final variation of the SOC of the battery is within 2 percenttpAnd Δ SOCthThe feasible region interval of (1); according to Δ SOCtpAnd Δ SOCthCan calculate the SOCpAnd SOCHTo determine the SOCpAnd SOCHThe feasible region interval of (1);
② determining the feasible region of calibration parameter related to power threshold value, and according to experience, PoThe value is small, the running time of the vehicle in the pure electric mode is short, and PoThe value is large, the running time of the vehicle in the EVT mode is short, and the P is ensured according to a required power-vehicle speed scatter diagramoThe feasible region interval comprises 50 to 80 percent of required power values; considering the economy of the whole vehicle and the frequent switching of the working mode, the reference delta SOCtpAnd SOCoSelecting the proportion and determining the delta PtpThe feasible region interval of (1); according to Δ PtpP can be calculatedpAnd further determine PpThe feasible region interval of (1);
③ determining charging power PchgIs a feasible domain of, according to experience, PchgSmall value, slow charging of the battery, PchgThe value is large, the battery can be overcharged, and P is further determined according to the charging power of the vehicle external charging equipmentchgThe feasible region interval of (1);
④ determining the threshold value n for the speed of the motor MG2 in the regenerative braking energy recovery modemoIs empirically, nmoThe value is small, the working efficiency of the motor MG2 is low, and nmoThe value is large, the braking recovery energy is not fully recovered, and n is ensured according to the efficiency curve of the motormoThe feasible region is in the range of higher motor efficiency;
⑤ determining the curve speed difference L of the gear boxsvEmpirically, the downshift curve is shifted left by about L from the upshift curvesvIndividual unit, then estimate L according to a specific shift strategysvCan be performed in the domain interval.

Claims (1)

1. A method for optimizing calibration parameters of a hybrid electric bus controller is characterized by comprising the following steps:
the method comprises the following steps of firstly, selecting a finished automobile constraint boundary and a calibration response, and specifically comprising the following steps:
①, taking the dynamic property of the hybrid electric bus as a whole vehicle constraint boundary;
②, taking hundred kilometers of theoretical oil consumption meeting the electric quantity balance condition as a calibration response;
and step two, deducing a hundred kilometer theoretical oil consumption formula obtained by average comprehensive energy transfer efficiency, and specifically comprising the following steps of:
① the hybrid power system is divided into a power source module, a transmission system module and a vehicle body module, wherein the power source module comprises an engine and a motor, the transmission system module comprises a planetary gear mechanism, a gearbox and a main reducer, and the vehicle body module mainly refers to a longitudinal dynamic model of the whole vehicle;
② deriving an average combined energy transfer efficiency η for the hybrid powertrain from the energy transfer relationships between the power source modules, the driveline modules, and the body modulestrAs shown in formula (1):
Figure FDA0002412233890000011
in the formula, EiceIndicating the actual supply of energy to the engine, EdchgRepresents the total energy of discharge of the battery, EchgRepresenting the total energy charged in the battery, ErgbRepresenting regenerative braking energy transmitted from the wheels to the battery via the transmission system, EwhExpressing the theoretical driving total energy of the cycle condition at the wheel, wherein delta SOC expresses the SOC difference value of the battery at the beginning and the end of the cycle condition simulation;
defining the actual energy E supplied by the engineiceAs shown in formula (2):
Figure FDA0002412233890000012
in the formula (f)eRepresenting one hundred kilometers theoretical oil consumption, be,avgRepresenting the average fuel consumption of the engine, C representing the conversion coefficient of units of fuel consumption, MeIndicating the fuel injection quantity, P, of the engineeRepresenting engine power;
defining the theoretical total driving energy E of the cycle condition at the wheelwhAs shown in formula (3):
Figure FDA0002412233890000013
in the formula, Ft,D(t) represents the theoretical driving force demand of the cycle condition, and v (t) represents the theoretical vehicle speed of the cycle condition;
③, deriving a hundred kilometers theoretical oil consumption calculation formula based on the average integrated energy transmission efficiency defined above, as shown in formula (4):
Figure FDA0002412233890000021
calculating the equivalent of the charging and discharging electric quantity of the battery to the theoretical oil consumption of one hundred kilometers, finally obtaining the theoretical oil consumption of one hundred kilometers under the condition of electric quantity balance as shown in the formula (5), and taking the theoretical oil consumption of one hundred kilometers under the condition of electric quantity balance as a calibration response;
Figure FDA0002412233890000022
thirdly, a whole vehicle energy management strategy based on the optimal control of the engine is formulated, and the method specifically comprises the following steps:
①, determining the driver demand torque, wherein the driver demand torque is determined by the pedal opening and the current vehicle speed, solving the current pedal opening by using a PID controller according to the target vehicle speed and the actual vehicle speed, calculating the system maximum output torque under the current vehicle speed, and multiplying the current pedal opening, the system maximum output torque under the current vehicle speed and the torque correction coefficient under the current vehicle speed to obtain the driver demand torque;
②, making system working mode switching rules, including switching rules among motion states, switching rules among working modes and switching rules of sub-modes under each working mode;
③ distributing system torque according to the working state of each component in different working modes of the system;
fourthly, optimizing calibration parameters according to the energy management strategy framework, and determining the required torque of the driver, the system working mode switching rule and different working modes according to the third stepThe system torque is distributed, and the selected calibration parameters are respectively the pedal opening torque correction coefficient function fξ(PS), mode switch SOC threshold value SOCoMode switching power threshold PoSOC lower limit value SOC for mode switching in EVT modepSOC upper limit value SOC for mode switching in EVT modeHLower limit value P of mode switching powerpSOC threshold margin lower limit value delta SOCtpSOC threshold margin upper limit value delta SOCthPower threshold margin Δ PtpCharging power PchgAnd a motor MG2 speed threshold n in the regenerative braking energy recovery modemoAnd the speed difference L of the lifting gear curve of the gearboxsv；
Fifthly, determining a feasible domain of the one-dimensional calibration parameters, which specifically comprises the following steps:
① determining the calibration parameter range related to battery characteristics, considering vehicle economy and preventing over discharge of battery, and further ensuring SOC according to the relation curve of battery internal resistance and SOCoThe feasible region is in the range with smaller internal resistance of the battery; considering the economy of the whole vehicle and the non-frequent switching of the working mode, determining the delta SOC according to the fact that the difference value of the initial and final variation of the SOC of the battery is within 2 percenttpAnd Δ SOCthThe feasible region interval of (1); according to Δ SOCtpAnd Δ SOCthCan calculate the SOCpAnd SOCHTo determine the SOCpAnd SOCHThe feasible region interval of (1);
② determining the calibration parameter feasible region related to the power threshold value, comprehensively considering the battery SOC balance and the pure electric mode as much as possible, and further ensuring P according to the required power-vehicle speed scatter diagramoThe feasible region interval comprises 50 to 80 percent of required power values; considering the economy of the whole vehicle and the frequent switching of the working mode, the reference delta SOCtpAnd SOCoSelecting the proportion and determining the delta PtpThe feasible region interval of (1); according to Δ PtpP can be calculatedpAnd further determine PpThe feasible region interval of (1);
③ determining charging power PchgConsidering the battery charging speed and the battery capacity, and according to the vehicle external connectionCharging power determination P of charging devicechgThe feasible region interval of (1);
④ determining the threshold value n for the speed of the motor MG2 in the regenerative braking energy recovery modemoThe feasible region of the motor MG2 is considered, the working efficiency and the regenerative braking energy recovery rate of the motor MG2 are considered, and n is ensured according to the efficiency curve of the motormoThe feasible region is in the range of higher motor efficiency;
⑤ determining the curve speed difference L of the gear boxsvEmpirically, the downshift curve is shifted left by about L from the upshift curvesvIndividual unit, then estimate L according to a specific shift strategysvCan be performed in the domain interval.
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