CN111581729A - Matching and integrating method for electric automobile power system - Google Patents
Matching and integrating method for electric automobile power system Download PDFInfo
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- CN111581729A CN111581729A CN202010404009.4A CN202010404009A CN111581729A CN 111581729 A CN111581729 A CN 111581729A CN 202010404009 A CN202010404009 A CN 202010404009A CN 111581729 A CN111581729 A CN 111581729A
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- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000004088 simulation Methods 0.000 claims abstract description 17
- 238000004364 calculation method Methods 0.000 claims abstract description 10
- 238000012360 testing method Methods 0.000 claims abstract description 10
- 238000013461 design Methods 0.000 claims abstract description 9
- 238000011160 research Methods 0.000 claims abstract description 9
- 238000012795 verification Methods 0.000 claims abstract description 8
- 238000005457 optimization Methods 0.000 claims description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 18
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 claims description 16
- 229910001416 lithium ion Inorganic materials 0.000 claims description 16
- 230000002068 genetic effect Effects 0.000 claims description 14
- 230000005540 biological transmission Effects 0.000 claims description 11
- 238000005516 engineering process Methods 0.000 claims description 9
- 230000010354 integration Effects 0.000 claims description 9
- 230000000694 effects Effects 0.000 claims description 8
- 238000011084 recovery Methods 0.000 claims description 5
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 4
- 238000011217 control strategy Methods 0.000 claims description 4
- 229910052744 lithium Inorganic materials 0.000 claims description 4
- 239000000126 substance Substances 0.000 claims description 4
- 238000011056 performance test Methods 0.000 claims description 3
- 238000007726 management method Methods 0.000 abstract description 5
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 230000001133 acceleration Effects 0.000 description 3
- 230000009194 climbing Effects 0.000 description 3
- 239000000306 component Substances 0.000 description 1
- 239000008358 core component Substances 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62D—MOTOR VEHICLES; TRAILERS
- B62D65/00—Designing, manufacturing, e.g. assembling, facilitating disassembly, or structurally modifying motor vehicles or trailers, not otherwise provided for
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/17—Mechanical parametric or variational design
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Abstract
The invention discloses a matching and integrating method of an electric automobile power system, which comprises modeling and theoretical calculation, system simulation, special research of a controller and test verification. The invention has the beneficial effects that: the method has the advantages of conveniently measuring and evaluating various indexes matched and integrated with the power system, reducing errors brought by the method in the process, conveniently realizing energy management and coordination control functions, planning the control mode of the whole automobile, improving the safety and the operation stability of the automobile and enabling the power performance of the electric automobile to achieve the optimal design.
Description
Technical Field
The invention relates to a matching and integrating method for a power system, in particular to a matching and integrating method for a power system of an electric automobile, and belongs to the technical field of power systems of electric automobiles.
Background
Compared with a fuel automobile, the main differences (differences) of the pure electric automobile are that four parts, a driving motor, a speed regulation controller, a power battery and a vehicle-mounted charger are arranged, and compared with a gas station, the pure electric automobile is provided with a public ultra-fast charging station, the quality difference of the pure electric automobile depends on the four parts, the value of the pure electric automobile also depends on the quality of the four parts, and the application of the pure electric automobile is directly related to the selection and the configuration of the four parts.
The motor driving control system is a main execution structure in the running of a new energy automobile, a driving motor and a control system thereof are one of core components (a battery, a motor and an electric control) of the new energy automobile, the driving characteristics of the driving motor determine main performance indexes of the running of the automobile, and the driving motor is an important component of the electric automobile, but the conventional power system of the electric automobile has a large problem in the aspects of the braking energy recovery control of a switched reluctance motor and the energy-power coordination control of a power battery energy storage system, so that the research and development or the perfection of the power system of the electric automobile which can simultaneously meet various performance requirements in the running process of the automobile and has the characteristics of firmness, durability, low manufacturing cost, high efficiency and the like are extremely important, and one of the links is the research of the matching and integration technology of.
Disclosure of Invention
The invention aims to solve the problems and provide a matching and integrating method of an electric automobile power system.
The invention realizes the purpose through the following technical scheme: a matching and integrating method of an electric automobile power system comprises the following steps:
step A: modeling and theoretical calculation, calculating power system parameters according to the requirements of finished automobile demand parameters by combining the kinematics principle and basic theoretical knowledge of the pure electric automobile, establishing a mechanical model of the pure electric automobile, determining the structure, the arrangement form and the control strategy of the power system, and providing a matching design method of the power system;
and B: the system simulation is used for carrying out simulation, testing and evaluating the power system, optimizing the transmission speed ratio by using a genetic algorithm, comparing dynamic parameters and driving range obtained by simulation before and after optimization to obtain a conclusion, and verifying the effect of the genetic algorithm in the aspect of optimization;
and C: the controller special research is carried out to develop a system vehicle control unit suitable for vehicle parameter optimization matching and build a complete vehicle control system framework with independent intellectual property rights;
step D: and (4) test verification, wherein the road test is carried out on the electric automobile according to GB/T18385 and 2016 electric automobile power performance test method.
Preferably, in order to ensure the accuracy of the calculated data and conveniently determine the highest vehicle speed, the climbing performance and the acceleration time through the calculation of the dynamic performance, and determine the constant-speed driving range and the working condition power consumption through the economic calculation, so that the data are more comprehensive, in the step a, the power system adopts a lithium battery as a main power source and recovers the braking energy, the parameter selection of the driving motor is in accordance with the torque and rotating speed characteristic requirement of the driving motor, the constant maximum torque is obtained at the starting time, namely the low rotating speed, and the constant higher power is obtained at the high rotating speed, and the selection of the maximum rotating speed of the driving motor is considered in combination with the reduction ratio of the transmission system, the efficiency of the driving motor and the continuous rotation characteristic.
Preferably, in order to optimize the power performance of the electric vehicle, the transmission speed ratio is optimized by using a genetic algorithm, dynamic parameters and driving range obtained by simulation before and after optimization are compared to obtain a conclusion, meanwhile, the effect of the genetic algorithm on the optimization aspect is verified, and the power system is evaluated.
Preferably, in order to conveniently realize the energy management and coordination control functions, a whole vehicle control mode is planned, and the safety and the operation stability of the vehicle are improved, in the step C, the controller optimizes the functions of energy control, drive control, braking energy recovery control, safety control and the like by using software, and grasps and uses the electric vehicle power matching key algorithm technology and the whole vehicle control technology for research.
Preferably, in order to ensure that the matching and integration of the power system of the electric automobile can be verified, the reasonability of data is ensured, errors are reduced, and the matching optimization effect of the power system of the sample automobile is conveniently verified, in the step D, according to the voltage grade and voltage range requirements of the motor of the electric automobile and the requirements of the geographic environment for use, a proper chemical system (a high-energy-density lithium ion battery, a high-power lithium ion battery, a low-temperature lithium ion battery or a high-temperature lithium ion battery) is selected, and then the verification is performed through a calculation formula.
The invention has the beneficial effects that: the matching and integration method of the power system of the electric automobile is reasonable in design, in the step A, the power system adopts a lithium battery as a main power source and recovers braking energy, the parameter selection of the driving motor is in accordance with the torque and rotating speed characteristic requirement of the driving motor, constant maximum torque is obtained when the driving motor is started, namely low rotating speed, constant higher power is obtained when the driving motor is high rotating speed, the maximum rotating speed of the driving motor is selected by combining the reduction ratio of a transmission system, the efficiency and the continuous rotation characteristic of the driving motor, the accuracy of calculated data is ensured, the highest speed, the climbing performance and the acceleration time are conveniently determined by calculating the dynamic performance, the constant driving mileage and the power consumption under the working condition are determined by calculating the constant speed, so that the data are more comprehensive, in the step B, on the basis of accurate theoretical modeling of the power system, ADVIOR software is utilized to simulate the performance of the parameters of the driving, obtaining a simulated speed map, an input motor power map, a power battery system SOC value map and the like, correcting system parameters according to a simulation result to enable the power performance of the electric vehicle to achieve the optimized design, optimizing a transmission speed ratio by using a genetic algorithm, comparing the power performance parameters obtained by simulation before and after optimization with the driving range to draw a conclusion, verifying the optimization function of the genetic algorithm, evaluating the power system, in the step C, realizing the functions of energy control, drive control, braking energy recovery control, safety control and the like by using software optimization by a controller, mastering and applying an electric vehicle power matching key algorithm technology and a whole vehicle control technology for research, conveniently realizing the functions of energy management and coordination control, planning a whole vehicle control mode, improving the safety and the operation stability of the vehicle, in the step D, according to the motor voltage level and voltage range requirements and the geographic environment requirements of the electric automobile, a proper chemical system (a high-energy-density lithium ion battery, a high-power lithium ion battery, a low-temperature lithium ion battery or a high-temperature lithium ion battery) is selected, and then verification is performed through a calculation formula, so that the matching and integration of the researched electric automobile power system can be verified, the reasonability of data is ensured, errors are reduced, and the matching optimization effect of the sample automobile power system is conveniently verified.
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FIG. 1 is a schematic view of the structure of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Referring to fig. 1, a matching and integrating method for an electric vehicle power system includes the following steps:
step A: modeling and theoretical calculation, calculating power system parameters according to the requirements of finished automobile demand parameters by combining the kinematics principle and basic theoretical knowledge of the pure electric automobile, establishing a mechanical model of the pure electric automobile, determining the structure, the arrangement form and the control strategy of the power system, and providing a matching design method of the power system;
and B: the system simulation is used for carrying out simulation, testing and evaluating the power system, optimizing the transmission speed ratio by using a genetic algorithm, comparing dynamic parameters and driving range obtained by simulation before and after optimization to obtain a conclusion, and verifying the effect of the genetic algorithm in the aspect of optimization;
and C: the controller special research is carried out to develop a system vehicle control unit suitable for vehicle parameter optimization matching and build a complete vehicle control system framework with independent intellectual property rights;
step D: and (4) test verification, wherein the road test is carried out on the electric automobile according to GB/T18385 and 2016 electric automobile power performance test method.
In the step A, a power system adopts a lithium battery as a main power source, braking energy is recovered, the parameter selection of a driving motor meets the torque and rotating speed characteristic requirement of the driving motor, constant maximum torque is obtained when the driving motor is started, namely, low rotating speed is obtained, constant higher power is obtained when the driving motor is high rotating speed, the maximum rotating speed of the driving motor is selected by considering the reduction ratio of a transmission system, the efficiency of the driving motor and the continuous rotation characteristic, the accuracy of calculated data is ensured, the highest speed, the climbing performance and the acceleration time are conveniently determined by calculating the power performance, and the constant speed driving mileage and the working condition power consumption are determined by calculating the economy, so that the data are more comprehensive, in the step B, on the basis of accurate theoretical modeling of the power system, ADVISOR software is utilized to simulate the parameter performance of the driving motor, the power source and the like, so as to obtain a simulated speed map, a power battery system SOC value diagram and the like, correcting system parameters according to a simulation result to enable the power performance of the electric automobile to achieve the optimized design, optimizing a transmission speed ratio by using a genetic algorithm, comparing power parameters and driving range obtained by simulation before and after optimization to draw a conclusion, verifying the effect of the genetic algorithm on optimization, and evaluating the power system, wherein in the step C, a controller utilizes software to optimize to realize functions of energy control, drive control, braking energy recovery control, safety control and the like, grasps and utilizes an electric automobile power matching key algorithm technology and a whole automobile control technology to research, conveniently realizes energy management and coordination control functions, plans a whole automobile control mode, improves the safety and the operation stability of the automobile, in the step D, according to the motor voltage grade and voltage range requirements and the using geographic environment requirements of the electric automobile, an appropriate chemical system (a high-energy-density lithium ion battery, a high-power lithium ion battery or a low-temperature lithium ion battery or a high-temperature lithium ion battery) is selected, and then verification is performed through a calculation formula, so that the matching and integration of the researched electric automobile power system can be verified, the reasonability of data is guaranteed, errors are reduced, and the matching optimization effect of the sample automobile power system is verified conveniently.
The working principle is as follows: calculating power system parameters by combining a pure electric vehicle kinematic principle and basic theoretical knowledge, establishing a mechanical model of the pure electric vehicle, determining a power system structure, an arrangement form and a control strategy, and providing a matching design method of the power system; the method comprises the steps of optimizing a transmission speed ratio by using a genetic algorithm, comparing dynamic parameters and driving range obtained by simulation before and after optimization to obtain a conclusion, verifying the optimization function of the genetic algorithm to realize energy management and coordination control functions, planning a whole vehicle control mode, improving the safety and operation stability of the vehicle, and enabling the dynamic performance of the electric vehicle to achieve the optimal design
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (5)
1. A matching and integrating method of an electric automobile power system is characterized in that: the method comprises the following steps:
step A: modeling and theoretical calculation, calculating power system parameters according to the requirements of finished automobile demand parameters by combining the kinematics principle and basic theoretical knowledge of the pure electric automobile, establishing a mechanical model of the pure electric automobile, determining the structure, the arrangement form and the control strategy of the power system, and providing a matching design method of the power system;
and B: the system simulation is used for carrying out simulation, testing and evaluating the power system, optimizing the transmission speed ratio by using a genetic algorithm, comparing dynamic parameters and driving range obtained by simulation before and after optimization to obtain a conclusion, and verifying the effect of the genetic algorithm in the aspect of optimization;
and C: the controller special research is carried out to develop a system vehicle control unit suitable for vehicle parameter optimization matching and build a complete vehicle control system framework with independent intellectual property rights;
step D: and (4) test verification, wherein the road test is carried out on the electric automobile according to GB/T18385 and 2016 electric automobile power performance test method.
2. The matching and integration method of the power system of the electric automobile according to claim 1, characterized in that: in the step A, the power system adopts a lithium battery as a main power source, the braking energy is recovered, the parameter selection of the driving motor is in accordance with the torque and rotating speed characteristic requirement of the driving motor, the constant maximum torque is obtained when the driving motor is started, namely the rotating speed is low, the constant higher power is obtained when the rotating speed is high, and the selection of the maximum rotating speed of the driving motor is considered by combining the reduction ratio of the transmission system, the efficiency of the driving motor and the continuous rotation characteristic.
3. The matching and integration method of the power system of the electric automobile according to claim 1, characterized in that: in the step B, on the basis of accurate theoretical modeling of the power system, ADVISOR software is utilized to simulate the performance of parameters such as a driving motor, a power source and the like to obtain a simulated speed map, an input motor power map, a power battery system SOC value map and the like, and system parameters are corrected according to a simulation result.
4. The matching and integration method of the power system of the electric automobile according to claim 1, characterized in that: in the step C, the controller realizes functions of energy control, drive control, braking energy recovery control, safety control and the like by software optimization, and grasps and utilizes an electric vehicle power matching key algorithm technology and a whole vehicle control technology for research.
5. The matching and integration method of the power system of the electric automobile according to claim 1, characterized in that: in the step D, according to the voltage grade and voltage range requirements of the motor of the electric automobile and the requirements of the geographical environment, a proper chemical system (a high-energy-density lithium ion battery, a high-power lithium ion battery, a low-temperature lithium ion battery or a high-temperature lithium ion battery) is selected, and then verification is performed through a calculation formula.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105608299A (en) * | 2016-03-04 | 2016-05-25 | 安徽工程大学 | Multi-objective optimization based parameter matching method for power system of battery electric vehicle |
| CN106599439A (en) * | 2016-12-08 | 2017-04-26 | 重庆大学 | Energy consumption-oriented parameter optimization and matching method for dual-motor power system of pure electric vehicle |
| CN111141532A (en) * | 2020-01-16 | 2020-05-12 | 常熟理工学院 | Multi-mode comprehensive test system for electric automobile |
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- 2020-05-13 CN CN202010404009.4A patent/CN111581729A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105608299A (en) * | 2016-03-04 | 2016-05-25 | 安徽工程大学 | Multi-objective optimization based parameter matching method for power system of battery electric vehicle |
| CN106599439A (en) * | 2016-12-08 | 2017-04-26 | 重庆大学 | Energy consumption-oriented parameter optimization and matching method for dual-motor power system of pure electric vehicle |
| CN111141532A (en) * | 2020-01-16 | 2020-05-12 | 常熟理工学院 | Multi-mode comprehensive test system for electric automobile |
Non-Patent Citations (1)
| Title |
|---|
| 赵广宣: "纯电动汽车动力传动系统匹配与整体优化研究" * |
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