CN111783228A - Energy-saving-oriented three-gear speed change system parameter matching optimization method for pure electric logistics vehicle - Google Patents
Energy-saving-oriented three-gear speed change system parameter matching optimization method for pure electric logistics vehicle Download PDFInfo
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Abstract
Firstly, based on the structural characteristics of a three-gear speed change system of the pure electric logistics vehicle, according to the power performance index of the pure electric logistics vehicle, the parameters of a driving motor and the speed change system are preliminarily matched; then establishing an optimization model taking the specific energy consumption of the vehicle under the conditions of 0-50km/h acceleration time and CHTC-LT circulation as an optimization target and taking parameters of a driving motor and parameters of a speed change system as variables, and solving the optimization model based on a layered gravity search algorithm (HGSA); provides a new idea for improving the dynamic property and the economical efficiency of the vehicle.
Description
Technical Field
The invention relates to the technical field of new energy automobile power systems, in particular to an energy-saving pure electric logistics vehicle three-gear speed change system parameter matching optimization method.
Background
The pure electric vehicle has received extensive attention because of its zero release, the noise is little, has the advantage of great energy-concerving and environment-protective potentiality, and along with the development of commodity circulation trade, pure electric vehicle has been applied to gradually replacing traditional commodity circulation car to this reduction cost of transportation. Most of the existing pure electric vehicles in the market adopt a speed reducer with a fixed speed ratio, and the requirements of the vehicles on the dynamic property and the economical efficiency cannot be well met. The multi-gear transmission can be used for adjusting the working state of the driving motor, improving the performance of a vehicle and reducing the performance requirement on the driving motor.
In the existing research, on one hand, the transmission ratio of the speed change system is optimized, the influence of the parameters of the driving motor on the performance of the vehicle is not fully considered, and on the other hand, the research is carried out on the transmission ratio of the speed change system under different motor schemes. The performance of the vehicle is determined by the driving motor and the speed change system together, and the influence of any element on the performance of the vehicle cannot be ignored, so that the parameters of the driving motor and the parameters of the speed change system are optimized simultaneously, the optimal parameters are sought, and the method has important significance for improving the power performance of the vehicle and prolonging the endurance mileage of the vehicle.
Disclosure of Invention
The invention aims to research the parameter matching optimization of a three-gear speed change system of a pure electric vehicle, obtain the optimized speed change system parameters and realize the comprehensive improvement of the dynamic property and the economical property of the vehicle.
The technical scheme adopted for achieving the aim of the invention is that the parameter matching optimization method for the three-gear speed change system of the energy-saving pure electric logistics vehicle comprises the following steps:
step 1: carrying out structural design on a three-gear speed change system of the pure electric logistic vehicle;
step 2: based on the structural characteristics of the three-gear speed change system of the pure electric vehicle in the step 1, the parameters of the three-gear speed change system are preliminarily matched;
and step 3: taking the acceleration time of the vehicle between 0 and 50km/h and the specific energy consumption of the vehicle when the vehicle runs under the CHTC-LT circulating working condition as an optimization target, taking the parameters of a driving motor and the parameters of a speed change system as variables, and establishing an optimization model comprehensively considering the dynamic property and the economical efficiency;
and 4, step 4: and (3) solving the multi-target optimization model of the energy-saving pure electric logistics vehicle three-gear speed change system in the step 3 by adopting an optimization algorithm to obtain optimal drive motor parameters and speed change system parameters.
Preferably, in step 3, the pure electric logistics vehicle is considered comprehensively in terms of power performance and economy, and the modeling process for parameter matching optimization of the three-gear speed change system of the pure electric logistics vehicle is as follows:
1. optimizing an objective
During the initial matching of the power system, the peak power and the maximum transmission ratio of the driving motor are mainly determined by the index requirement of the vehicle for 0-50km/h of acceleration time, and the acceleration performance of the vehicle also determines the maximum climbing gradient of the vehicle. Therefore, the maximum climbing gradient and the maximum vehicle speed of the vehicle can be treated as constraint conditions, and the acceleration time of the vehicle of 0-50km/h and the specific energy consumption of the vehicle when the vehicle runs under the CHTC-LT circulating working condition are selected as optimization targets.
(1) Acceleration time of 0-50km/h
The maximum on-wheel driving force obtained by the vehicle and the running resistance borne by the vehicle are main factors influencing the 0-50km/h acceleration time of the pure electric logistics vehicle.
Wherein, taAcceleration time of 0-50km/h, m0For empty mass of vehicle, mcFor cargo weight, vs1Upshift speed, v, for 1-2 gearss2Upshift speed for 2-3 gear, Ft1Is 0 to t1Period of vehicle driving force, Ft2Is t1To t2Period of vehicle driving force, FbFor vehicle runningReceived resistance, vmaxThe maximum speed of the vehicle is set as the vehicle speed,1、2、3the equivalent mass inertia coefficients of the three phases of the vehicle are respectively.
(2) Specific energy consumption under cyclic working condition
The mass of the pure electric logistics vehicle researched in the paper is 4495kg, so that the CHTC-LT driving circulation working condition in the new national standard CATC circulation working condition is selected as the driving circulation working condition of the pure electric logistics vehicle. The specific energy consumption under the cycle condition is used as an index for measuring the economic performance of the vehicle, and the specific energy consumption under the cycle condition represents the energy consumed by the running unit mileage (km) of the pure electric logistics vehicle under the CHTC-LT condition, and the unit is kW.h/km. The specific energy consumption under the circulating working condition is as follows:
wherein, ECFor specific energy consumption under the circulation working condition, m is the whole vehicle mass of the pure electric vehicle, g is the gravity acceleration, f is the rolling resistance coefficient of the vehicle, β is the ramp angle of the driving road, CDThe wind resistance coefficient of the pure electric vehicle is A, the windward area of the pure electric vehicle is A, the equivalent mass inertia coefficient of the pure electric vehicle is A, t is a time variable, rho is an air density, and the value of the air density under the standard atmospheric pressure is rho which is 1.2258N S2·m-4,LCThe total travel distance of the CHTC-LT cycle working condition, v (t) the speed of the pure electric vehicle at the moment t, F (t) the driving force provided by a power assembly during the running of the vehicle, ηTFor transmission efficiency, ηM(t) is the efficiency of the drive motor at time t, calculated as follows:
wherein, PiOutput power for a certain operating point of the drive motor, PCuCopper loss, P, for driving the motor at this operating pointeIs eddy current loss, PhIs hysteresis loss, PmFor mechanical wear, PmaxTo drive the motor peak power, PNFor rating the drive motor, niTo drive the motor speed, nNFor rated speed of the drive motor, neThe rated rotating speed of the driving motor.
2. Optimizing variables
The efficiency of the driving motor at each working point is influenced by three parameters of the peak power, the rated rotating speed and the rated power of the driving motor. The driving force output by the power assembly under each gear can be influenced by different transmission ratios and peak torque of the driving motor, so that the power performance of the vehicle is influenced; the coordinated matching of the parameters of the speed changing system and the parameters of the driving motor can enable the vehicle to obtain good power performance, and meanwhile, the driving motor can work in a high-efficiency area more, so that the energy efficiency of the whole vehicle is improved, the endurance mileage of the pure electric logistics vehicle is prolonged, and the transportation cost of the pure electric logistics vehicle is reduced.
The increase of the peak power and the maximum rotating speed of the motor of the driving motor inevitably leads to the increase of the cost of the driving motor, so the invention uses the rated power P of the driving motor on the premise of not changing the peak power and the maximum rotating speed of the driving motorNDriving rated speed nNAnd a three-gear speed reduction ratio i of the speed change system3With the characteristic parameters α of the NGW epicyclic as the optimization variables:
X=[X1,X2,X3,X4]=[PN,nN,i3,α]
3. constraint conditions
(1) Maximum climbing slope constraint
The driving force transmitted to the wheels by the power assembly needs to be greater than the resistance borne by the vehicle when the vehicle runs at the climbing speed, namely:
wherein, TmaxTo drive the peak torque of the motor, βmaxMaximum ramp angle of the road, i1For the gear system, the gear reduction ratio is set, and r is the wheel radius.
(2) Maximum vehicle speed constraint
When the pure electric logistics vehicle runs on a horizontal windless road surface, the peak power of the driving motor needs to meet the requirement of the vehicle on the output power of the driving motor when running at the highest speed, and in order to ensure that the vehicle runs at the required highest speed, the highest gear transmission ratio of the speed change system needs to meet the constraint:
wherein n ismaxThe maximum rotation speed of the driving motor.
(3) Wheel slip restraint
The vehicle researched by the invention is a rear-drive vehicle, and in the vehicle starting and rapid acceleration stages, in order to prevent wheels from slipping and improve the vehicle stability, the maximum torque transmitted to the wheels needs to be limited:
wherein mu is a wheel slip coefficient, and the maximum value is 1.02; l is the wheelbase of the front axle and the rear axle of the pure electric animal flow vehicle, and 3308mm is taken; l is12105mm is taken as the distance from the mass center of the pure electric animal flow vehicle to the front axle of the vehicle; h isgThe mass center height of the pure electric animal current vehicle in the full-load state is 930 mm.
(4) Boundary constraint
The feasible region of each optimized variable is reduced, the iteration speed of the optimization algorithm can be accelerated, and the fast solving of the optimization model is facilitated, so that the boundary of each optimized variable is constrained by combining the analysis of the parameter matching process of the power system of the pure electric vehicle.
20≤PN≤60
2000≤nN≤4000
8≤i3≤9.55
1.4≤α≤2
In order to ensure smooth gear shifting of the vehicle in the driving process, the transmission ratio of two adjacent gears in the speed change system is less than 2, namely in/in+1≤2。
The comprehensive performance parameter optimization model comprises the following steps:
minF(PN,nN,i3,α)=(minta,minEC)
preferably, in step 4, the optimization model is solved by using a hierarchical gravity search algorithm. Setting parameters of an algorithm, setting the dimension d of a solution in a parameter optimization model of the variable speed system to be 4, setting the size n of an initial bottom layer quality point group to be 50, and setting a universal gravitation coefficient G 0100, 100 is the universal gravitation number iteration step length L, and 50 is the maximum iteration time T. The flow of the hierarchical gravity search algorithm is shown in fig. 2.
Compared with the prior art for optimizing the speed change system of the electric vehicle, the invention has the beneficial effects that:
the invention comprehensively considers the influence of the transmission ratio of the speed change system and the parameters of the driving motor on the vehicle performance, and firstly, the parameters of the driving motor and the speed change system are preliminarily matched according to the power performance index of the pure electric logistics vehicle. And then, by taking the specific energy consumption of the vehicle under the conditions of 0-50km/h acceleration time and CHTC-LT cycle as an optimization target and taking the parameters of the driving motor and the parameters of the speed change system as variables, constructing an energy-saving-oriented multi-target matching optimization model of the three-gear speed change system parameters of the pure electric logistics vehicle, and providing a new idea for improving the comprehensive performance of the vehicle. The optimization model is solved based on a layered gravity search algorithm (HGSA), a simulation model is established by using an MATLAB/Simulink simulation platform, vehicle performances determined by parameters of the speed change system before and after optimization are compared, and simulation results show that the energy-saving pure electric logistics vehicle three-gear speed change system parameter matching optimization method effectively improves the dynamic property and the economical property of the vehicle.
Drawings
FIG. 1 shows a flow of a parameter matching optimization method for a three-gear speed change system of an energy-saving pure electric logistics vehicle
FIG. 2 optimization flow of hierarchical gravity search algorithm
FIG. 3 vehicle dynamics simulation model
FIG. 4 vehicle acceleration time simulation model
FIG. 5 Power Performance simulation results
FIG. 60-50 km/h acceleration simulation results
FIG. 7 simulation model of the whole vehicle
FIG. 8 CHTC-LT working condition energy consumption simulation result
Detailed Description
The present invention will be further described with reference to the accompanying drawings and examples, but it should not be construed that the scope of the above-described subject matter is limited to the examples. Various substitutions and alterations can be made without departing from the technical idea of the invention and the scope of the invention is covered by the present invention according to the common technical knowledge and the conventional means in the field.
According to the implementation, a MATLAB/Simulink simulation platform is used for establishing a vehicle power performance simulation model and a whole vehicle model, simulation analysis and comparison are carried out on power system parameters before and after optimization based on an optimization result shown in a table 1, and the acceleration time of the vehicle is 0-50km/h and the energy consumption condition of the CHTC-LT circulation working condition are verified.
TABLE 1 optimization results
In order to verify the validity of the optimization result, the resistance moment received by the vehicle when the vehicle runs on a flat road and a 30% slope road and the driving moment provided by the power system are analyzed and calculated according to the optimized parameters of the power system, and a power performance simulation model shown in figure 3 and a vehicle 0-50km/h acceleration time simulation model shown in figure 4 are established. As can be seen from FIG. 5, due to the change of the transmission ratio of the 3-gear, the maximum vehicle speed of the vehicle can reach 99.8km/h, and compared with the parameter primary matching stage, the maximum driving speed of the vehicle is improved by 5.67%; meanwhile, the peak torque of the driving motor and the transmission ratio of the 1-gear of the speed change system are increased simultaneously, so that the maximum starting gradient of the vehicle is greatly improved from 32.69% to 46.21%, the lifting degree is 41.3%, the peak power of the driving motor is not optimized as a variable, and the vehicle speed of the vehicle running on a road surface with 30% of gradient is still 19.5km/h due to power limitation. Fig. 6 is a comparison graph of 0-50km/h acceleration time of the pure electric logistics vehicles before and after optimization, and it can be seen that the time required for the vehicle to accelerate from rest to 50km/h before optimization is 8.47s, the acceleration time required after optimization is 7.92s, and the optimized lift is 6.69%.
A whole vehicle forward simulation model shown in FIG. 7 is established to calculate the situation that vehicle energy consumption of a pure electric logistics vehicle changes with mileage under the CHTC-LT driving cycle condition. FIG. 8 is a comparison graph of CHTC-LT driving cycle working condition energy consumption of the pure electric logistics vehicles before and after optimization, and the specific energy consumption of the vehicle driving cycle before optimization can be calculated to be 0.4798 kW.h/km, the specific energy consumption after optimization is 0.4729 kW.h/km, the lifting degree is 1.44%, and the economic performance of the vehicle is improved.
In summary, under the condition that the peak power of the driving motor is constant, the acceleration time of 0-50km/h of the vehicle can be shortened by 6.69% by increasing the peak torque of the motor and the maximum transmission ratio of the speed change system, and the maximum starting gradient of the vehicle can be improved to a certain extent. By optimizing the parameters of the driving motor and simultaneously matching the multi-gear transmission to adjust the working range of the driving motor, simulation analysis shows that the optimized parameters of the speed changing system are 1.44 percent lower than the energy consumption of the driving cycle relative to the initial matching parameters, and the energy efficiency of the whole vehicle is improved to a certain extent.
Claims (2)
1. An energy-saving-oriented pure electric logistics vehicle three-gear speed change system parameter matching optimization method is characterized by comprising the following steps:
step 1: carrying out structural design on a three-gear speed change system of the pure electric logistic vehicle;
step 2: based on the structural characteristics of the three-gear speed change system of the pure electric vehicle in the step 1, the parameters of the three-gear speed change system are preliminarily matched;
and step 3: taking the acceleration time of the vehicle between 0 and 50km/h and the specific energy consumption of the vehicle when the vehicle runs under the CHTC-LT circulating working condition as an optimization target, taking the parameters of a driving motor and the parameters of a speed change system as variables, and establishing an optimization model comprehensively considering the dynamic property and the economical efficiency;
and 4, step 4: and (3) solving the multi-target optimization model of the energy-saving pure electric logistics vehicle three-gear speed change system in the step 3 by adopting an optimization algorithm to obtain optimal drive motor parameters and speed change system parameters.
2. The energy-saving-oriented pure electric logistics vehicle three-gear speed change system parameter matching optimization method according to claim 1, characterized in that: in step 3, the modeling process is as follows:
(1) optimizing an objective
1) Acceleration time of 0-50km/h
Wherein, taAcceleration time of 0-50km/h, m0For empty mass of vehicle, mcFor cargo weight, vs1Upshift speed, v, for 1-2 gearss2Upshift speed for 2-3 gear, Ft1Is 0 to t1Period of vehicle driving force, Ft2Is t1To t2Period of vehicle driving force, FbResistance received for vehicle travel, vmaxThe maximum speed of the vehicle is set as the vehicle speed,1、2、3equivalent mass inertia coefficients of three stages of the vehicle are respectively;
2) specific energy consumption under cyclic working condition
Wherein E isCFor specific energy consumption under the circulation working condition, m is the whole vehicle mass of the pure electric vehicle, g is the gravity acceleration, f is the rolling resistance coefficient of the vehicle, β is the ramp angle of the driving road, CDThe wind resistance coefficient of the pure electric vehicle is A, the windward area of the pure electric vehicle is A, the equivalent mass inertia coefficient of the pure electric vehicle is A, t is a time variable, rho is an air density, and the value of the air density under the standard atmospheric pressure is rho which is 1.2258N S2·m-4,LCTotal distance traveled for CHTC-LT cycle, v: (C-LT)t) is the speed of the pure electric vehicle at the moment t, F (t) is the driving force provided by a power assembly during the running process of the vehicle, ηTFor transmission efficiency, ηM(t) is the efficiency of the drive motor at time t, calculated as follows:
wherein, PiOutput power for a certain operating point of the drive motor, PCuCopper loss, P, for driving the motor at this operating pointeIs eddy current loss, PhIs hysteresis loss, PmFor mechanical wear, PmaxTo drive the motor peak power, PNFor rating the drive motor, niTo drive the motor speed, nNFor rated speed of the drive motor, neRated speed for the drive motor;
(2) optimizing variables
To drive the motor with rated power PNDriving rated speed nNAnd a three-gear speed reduction ratio i of the speed change system3With the characteristic parameters α of the NGW epicyclic as optimization variables, namely:
X=[X1,X2,X3,X4]=[PN,nN,i3,α]
(3) constraint conditions
1) Maximum climbing slope constraint
Wherein, TmaxTo drive the peak torque of the motor, βmaxMaximum ramp angle of the road, i1A gear reduction ratio of the speed change system is set, and r is the radius of a wheel;
2) maximum vehicle speed constraint
Wherein n ismaxThe maximum rotating speed of the driving motor;
3) wheel slip restraint
Wherein mu is a wheel slip coefficient; l is the wheelbase of the front axle and the rear axle of the pure electric logistic vehicle; l is1The distance from the mass center of the pure electric animal flow vehicle to the front axle of the vehicle; h isgThe height of the mass center of the pure electric animal current vehicle in a full-load state;
4) boundary constraint
20≤PN≤60
2000≤nN≤4000
8≤i3≤9.55
1.4≤α≤2。
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114861332A (en) * | 2022-07-05 | 2022-08-05 | 清华大学 | Topological structure and parameter layering optimization method of electric drive system of dual-motor transmission |
CN118013867A (en) * | 2024-04-09 | 2024-05-10 | 西北工业大学 | Large-power span variable-speed underwater propulsion motor, design method thereof and underwater equipment |
Citations (10)
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 |
CN108491670A (en) * | 2018-04-17 | 2018-09-04 | 常熟理工学院 | A kind of parameter matching of electronic logistic car driving motor and optimization method |
CN108984812A (en) * | 2017-06-05 | 2018-12-11 | 湖南科技大学 | A kind of power matching method suitable for small-sized pure electric tractor |
CN110203075A (en) * | 2019-05-31 | 2019-09-06 | 武汉理工大学 | A kind of four-wheel hub motor Vehicular system power matching method |
US20190318051A1 (en) * | 2016-07-13 | 2019-10-17 | Avl List Gmbh | Method for simulation-based analysis of a motor vehicle |
CN110688477A (en) * | 2019-10-10 | 2020-01-14 | 华夏幸福产业投资有限公司 | Prediction method, device, equipment and storage medium in technical hotspot field |
CN110717218A (en) * | 2019-09-18 | 2020-01-21 | 北京理工大学 | Electric drive vehicle distributed power drive system reconstruction control method and vehicle |
CN110941875A (en) * | 2019-11-11 | 2020-03-31 | 常熟理工学院 | Full hybrid vehicle energy efficiency optimization control method of adaptive asynchronous particle swarm |
CN111199311A (en) * | 2019-12-24 | 2020-05-26 | 国网江苏省电力有限公司扬州供电分公司 | Residential area charging facility power optimization method |
-
2020
- 2020-07-02 CN CN202010627960.6A patent/CN111783228B/en active Active
Patent Citations (10)
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 |
US20190318051A1 (en) * | 2016-07-13 | 2019-10-17 | Avl List Gmbh | Method for simulation-based analysis of a motor 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 |
CN108984812A (en) * | 2017-06-05 | 2018-12-11 | 湖南科技大学 | A kind of power matching method suitable for small-sized pure electric tractor |
CN108491670A (en) * | 2018-04-17 | 2018-09-04 | 常熟理工学院 | A kind of parameter matching of electronic logistic car driving motor and optimization method |
CN110203075A (en) * | 2019-05-31 | 2019-09-06 | 武汉理工大学 | A kind of four-wheel hub motor Vehicular system power matching method |
CN110717218A (en) * | 2019-09-18 | 2020-01-21 | 北京理工大学 | Electric drive vehicle distributed power drive system reconstruction control method and vehicle |
CN110688477A (en) * | 2019-10-10 | 2020-01-14 | 华夏幸福产业投资有限公司 | Prediction method, device, equipment and storage medium in technical hotspot field |
CN110941875A (en) * | 2019-11-11 | 2020-03-31 | 常熟理工学院 | Full hybrid vehicle energy efficiency optimization control method of adaptive asynchronous particle swarm |
CN111199311A (en) * | 2019-12-24 | 2020-05-26 | 国网江苏省电力有限公司扬州供电分公司 | Residential area charging facility power optimization method |
Non-Patent Citations (1)
Title |
---|
李聪波; 张弛; 屈世阳; 胡曾明: "考虑道路坡度与车辆载重的纯电动物流车综合性能换挡规律", 《中国机械工程》, pages 275 - 283 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114861332A (en) * | 2022-07-05 | 2022-08-05 | 清华大学 | Topological structure and parameter layering optimization method of electric drive system of dual-motor transmission |
CN118013867A (en) * | 2024-04-09 | 2024-05-10 | 西北工业大学 | Large-power span variable-speed underwater propulsion motor, design method thereof and underwater equipment |
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