CN105005222A - New-energy electric automobile overall performance improving system and method based on big data - Google Patents
New-energy electric automobile overall performance improving system and method based on big data Download PDFInfo
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- CN105005222A CN105005222A CN201510324855.4A CN201510324855A CN105005222A CN 105005222 A CN105005222 A CN 105005222A CN 201510324855 A CN201510324855 A CN 201510324855A CN 105005222 A CN105005222 A CN 105005222A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
- B60R16/023—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for transmission of signals between vehicle parts or subsystems
- B60R16/0231—Circuits relating to the driving or the functioning of the vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/25—Pc structure of the system
- G05B2219/25314—Modular structure, modules
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
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Abstract
The invention discloses a new-energy electric automobile overall performance improving system and method based on big data. The system comprises a local system, a big data processing platform, and a remote virtual system. The local system is used for driving and controlling a local vehicle, and uploading relevant parameters of the local vehicle to the big data processing platform via a monitoring network. The big data processing platform is used for performing data classification, statistic, analysis, storage, and excavation on the relevant parameters of the local vehicle. The remote virtual system is used for establishing a virtual model of a vehicle, a motor, a battery, and a motor controller, using the various parameters processed by the big data processing platform as an input of the virtual model, optimizing the virtual model by using a vehicle optimum parameter as an output target, and downloading various parameters generated by the virtual model to the local system. The local system can be optimized according to the downloaded various parameters, and returns the downloaded various parameters to a manufacturer in order to provide data reference for the production process of the manufacturer and achieve improvement in the new-energy electric automobile overall performance.
Description
Technical field
The present invention relates to the New-energy electric vehicle vehicle performance elevator system based on large data and method.
Background technology
Along with increasing rapidly of Global Auto recoverable amount, the pressure facing the energy, environment and safety strengthens day by day.From sustainable development, the four large automobile public hazards that automobile industry must solve the energy, pollution, safety and the whole world that blocks up is generally acknowledged, low carbonization, informationization and intelligent vehicle are considered to final solution.In new-energy automobile, within 2014, the whole year sold 74763 by New Energy Sources In China automobile, increases by 323.8% on a year-on-year basis.Become global new-energy automobile and promote the country be number two, estimate that China in 2015 will become the maximum country of global new-energy automobile sales volume.
Although new-energy automobile obtains the active support of the government in China, also there is a lot of problems in the new-energy automobile industry of China, limits new-energy automobile in the development of China and popularization.These problems comprise:
1. now the new-energy automobile enterprise of China completes mainly through experience, software emulation and basic test when designing new-energy automobile, lack promoted by the analysis of real data, the means of optimal design vehicle parameters.
2. the safety problem of electrokinetic cell itself.Electrokinetic cell reserve power mechanism is galvanochemistry, and electrochemical reaction process exists potential safety hazard.This is because the chemical characteristic of electrokinetic cell itself determines, does not also have a kind of electrokinetic cell can avoid inherently safe problem completely.But how can better normally work by monitoring battery, and the cost that do not increase of trying one's best needs the analysis of large data to support, to carry out real-time management to the safety of electrokinetic cell.
3. the burst mode of electrokinetic cell is unreasonable, easily potential safety hazard occurs.Current New-energy electric vehicle electrokinetic cell used is all undertaken becoming a system in groups by the mode of series and parallel by thousands of little battery.Electrokinetic cell needs the problem such as series-parallel system, heat management, vibration solving battery in groups.At present, also do not have a kind of burst mode of electrokinetic cell to think the most rational, how to evaluate existing battery burst mode and instruct optimization battery burst mode to need the analysis of large data to support.
Summary of the invention
Object of the present invention be exactly in order to solve the problem, the New-energy electric vehicle vehicle performance elevator system based on large data and method are provided, it have solve the performance boost of New-energy electric vehicle life-cycle closed loop design, checking, optimization problem advantage.
To achieve these goals, the present invention adopts following technical scheme:
Based on the New-energy electric vehicle vehicle performance elevator system of large data, comprising:
Local system, for power drive and the control of local vehicle, is uploaded to large data processing platform (DPP) by the correlation parameter of local vehicle by monitor network;
Monitor network, for being transferred to large data processing platform (DPP) by the correlation parameter of local vehicle by the mode of radio communication;
Large data processing platform (DPP), for carrying out Data classification, statistics, analysis, storage and excavation by the correlation parameter of vehicle;
Remote virtual system, for setting up vehicle, motor, the dummy model of battery and electric machine controller, using the input of the parameters after large data processing platform (DPP) process as dummy model, by setting up vehicle optimized parameter as output target, dummy model is optimized, the parameters that dummy model generates is downloaded to local system, local system both can complete the optimization of local system according to the parameters downloaded, the parameters of download can be fed back to manufacturer again, data reference is provided to the production run of manufacturer, thus realize the lifting of entire new energy automobile performance.
The correlation parameter of described local vehicle, comprising: current location, distance travelled, the speed of a motor vehicle, throttle, brake, gear, turn to, motor speed, revolve variable element, power of motor, Motor torque, electrokinetic cell total voltage, total current, single cell battery voltage, battery temperature, the internal resistance of cell, euqalizing current, charging voltage or charging current.
Described vehicle optimized parameter comprises: vehicle acceleration, max. speed, the longest continual mileage, car weight, power consumption and ramp angle.
Described local system, comprising: entire car controller, electrokinetic cell, motor, electric machine controller, battery management system, charging set.
Described entire car controller, operation for realizing driver according to accelerator pedal position, gear, brake pedal force is intended to and all parts controlling car load carries out co-ordination, and entire car controller will speed up pedal position, braking force, gear information, steering wheel angle parameter send into monitor network;
Described electrokinetic cell is the energy source driving vehicle to travel;
Described motor is the driver driving vehicle to travel;
Described electric machine controller controls machine operation controller, electric machine controller by motor speed, moment of torsion, power, temperature, revolve the parameter such as varying signal, failure code and send into monitor network;
Described battery management system, be detect, control, the control system that normally works of uniform power battery system, the parameters such as electrokinetic cell total voltage, total current, single cell battery voltage, battery temperature, the internal resistance of cell, balanced mode, euqalizing current are sent into monitor network by battery management system;
Described charging set is the controller of power battery charging, and charging voltage, charging current, charge mode are sent into monitor network by charging set.
Described monitor network, comprising: the telecommunications networks such as GPS, GPRS, 3G, 4G, WIFI and CAN, LIN, Flexray wait for bus interior communication network, and monitor network is used for the data received from local system to pass to large data processing platform (DPP).
Described large data processing platform (DPP), comprising: cloud memory module, cloud administration module, large data processing module and data-mining module.
Described cloud memory module, for the storage of the associated parameter data of local vehicle, comprising: the write of database, access;
Described cloud administration module, for managing large data processing platform (DPP), comprising: the storage unit of cloud platform, the distribution of computational resource and management, user management;
Described large data processing module, for the conversion of the correlation parameter of local vehicle, grouping, tissue, calculating, retrieval, sequence.
Conversion: correlation parameter is converted to the form that machine can receive.Such as two octets are merged and be converted into 16 bit bytes;
Grouping: by carrying out packet for information about.Comprise for information about: battery information, motor information, whole vehicle information;
Tissue: disposal data or with some method arranging data, to process.Such as according to uplink time, the total voltage of battery and electric current are carried out to the display of two dimensional form;
Calculate: carry out various arithmetic sum logical operation, to obtain further information.Such as total current is carried out integration according to the time, calculate the electricity of battery consumption;
Retrieval: the information finding out user's request by the requirement of user.Such as retrieve the battery total voltage of section sometime;
Sequence: data are lined up order by setting requirement, such as sorts according to the size of time sequencing to charging voltage.
Described data-mining module, for excavating important information in the data from large data processing module process.As by the information prediction battery life information such as total voltage, total current, internal resistance, temperature analyzing battery.The like can excavate the important information such as failure cause, electrical machinery life, battery incipient fault of motor.
Described remote virtual system, comprising: car load allocation models, battery be model, motor model, Electric Machine Control model, battery model, charging strategy model in groups.
Described car load allocation models, using complete vehicle quality, max. speed, maximum acceleration, course continuation mileage, maximumly to turn to, the parameter such as maximum climbing as known quantity as input, the configuration parameter of the electrokinetic cell needed for calculating, drive motor, braking energy feedback strategy, brake system and charging set;
Described battery model in groups, using the series and parallel mode of battery, single battery quantity, single battery nominal voltage, battery arrangement mode as known quantity as input, using battery total voltage, battery single-unit voltage, single battery internal resistance, charging and discharging currents, euqalizing current, battery case temperature, battery vibration as dynamically measuring as input, predict the incipient fault after battery in groups and life-span;
Described motor model, using the design parameter of motor as known input quantity, using motor internal electric current, voltage, power and torque as dynamic input quantity, calculates the efficiency of motor, the incipient fault of pre-measured motor and life-span;
Described Electric Machine Control model, for Permanent Magnet Synchronous Motor Controller, for simulated machine control strategy, by throttle signal, brake signal, revolve varying signal, dynamic battery voltage signal, motor temperature, as input, is calculated by motor control strategy, as speed closed loop constant voltage constant frequency control strategy, slip frequency control strategy, based on the vector control strategy of field orientation and Strategy of Direct Torque Control, calculate the PWM dutycycle of U/V/W three-phase voltage, realize the simulation of Electric Machine Control;
Described single battery model, using single battery voltage, battery ohmic internal resistance as input, sets up as battery RC equivalent model, for analog simulation single battery dump energy and battery life;
Described charging strategy model, using externally fed voltage, current power battery total voltage, charging voltage, charging current as input, calculates the duration of charging, calculates the efficiency of charging strategy modes such as (as:) constant voltage, constant current, pulses.
Based on the New-energy electric vehicle vehicle performance method for improving of large data, comprise the steps:
Step (1): the entire car controller of local system, electric machine controller, battery manager, charging set realize interconnection by the internal bus of vehicle, local system by monitor network by the operational factor teletransmission of vehicle to large data processing platform (DPP);
Step (2): by large data processing and the large data mining of large data processing platform (DPP), revises and improves remote virtual system;
Step (3): by all kinds of parameter downloads perfect for remote virtual system correction to entire car controller, electric machine controller, battery manager, charging set, local controller and local system is optimized by real vehicle checking, if reach optimum index, terminate;
If do not reach optimum index, from step (1), carry out loop optimization, thus realize the closed-loop control promoting Full Vehicle System parameter;
If reach optimum index, then the battery group parameter of optimization, the parameter of electric machine, battery parameter are fed back to parts producer, carry out the perfect of related components.
The step of described step (2) is:
Step (2-1): large data are carried out carry out classifying, store, add up, change, calculate and transmitting according to whole-car parameters, the parameter of electric machine, Motor control parameters, battery group parameter, battery parameter, charge parameter;
Step (2-2): whole-car parameters is inputted car load allocation models, the configuration parameter of the electrokinetic cell needed for calculating, drive motor, braking energy feedback strategy, brake system and charging set;
Step (2-3): the parameter of electric machine is inputted motor model, calculates the efficiency of motor, the incipient fault of prediction and calculation motor and life-span;
Step (2-4): Motor control parameters is inputted Electric Machine Control model, calculates the PWM dutycycle of U/V/W three-phase voltage;
Step (2-5): by battery group parameter input battery model in groups, prediction and calculation battery in groups after incipient fault and the life-span;
Step (2-6): by single battery parameters input battery model, prediction and calculation emulation single battery dump energy and battery life;
Step (2-7): charge parameter is inputted charging strategy model, calculates duration of charging and charge efficiency;
In step (2) process the incipient fault of prediction and calculation motor and life-span, prediction and calculation battery in groups after incipient fault and life-span, prediction and calculation emulation single battery dump energy and battery life institute obtaining value be not an accurate value, a but value predicted.For making predicted value more accurate, need to carry out accurately predicting by the mode of large data processing or data mining.
Beneficial effect of the present invention:
Native system passes through the cloud platform management center of new-energy automobile and large data processing centre (DPC), set up the local controller of entire new energy automobile and key components and parts and local model and remote controllers and long-range model, managed by the cloud of new-energy automobile, cloud store, large data processing and data mining, realize the local management of new-energy automobile and the closed-loop system of long-range optimization.By data processing and the excavation in high in the clouds, optimize remote dummy controller and whole-car parameters, and the parameter after checking optimization or model are downloaded to local controller, and guide car load and the parts design of auto vendor and parts producer, thus promote vehicle performance and the quality of new-energy automobile.
Another beneficial effect of native system is the life-cycle management by electrokinetic cell.The design of battery cell monitoring parameter, the design of battery group schema and the management of the health parameters of battery life-cycle can be instructed by electrokinetic cell real-time monitoring data and data processing and data mining, provide data supporting for the design of electrokinetic cell, management, recovery and echelon utilize.
Described electrokinetic cell life-cycle management by the Real-time Collection of electric battery data, transmission, large data analysis are excavated for the design of electrokinetic cell monitoring parameter, battery in groups, to reclaim and echelon utilizes and provides effective technological means.
Remote virtual system is set up different controllers and the dummy model of system, by the data of the real vehicle collected, these Virtual Controllers and model are optimized, controller parameter after optimization and model are downloaded in local controller, and provide the method for design optimization for car load producer and parts producer, thus realize the lifting of New-energy electric vehicle performance.
Accompanying drawing explanation
Fig. 1 is system construction drawing of the present invention;
Fig. 2 is specific embodiments of the invention.
Embodiment
Below in conjunction with accompanying drawing and embodiment, the invention will be further described.
As shown in Figure 1, based on the New-energy electric vehicle vehicle performance elevator system of large data, comprising:
Local system, for power drive and the control of local vehicle, is uploaded to large data processing platform (DPP) by the correlation parameter of local vehicle by monitor network;
Monitor network, for being transferred to large data processing platform (DPP) by the correlation parameter of local vehicle by the mode of radio communication;
Large data processing platform (DPP), for carrying out Data classification, statistics, analysis, storage and excavation by the correlation parameter of vehicle;
Remote virtual system, for setting up vehicle, motor, the dummy model of battery and electric machine controller, using the input of the parameters after large data processing platform (DPP) process as dummy model, by setting up vehicle optimized parameter as output target, dummy model is optimized, the parameters that dummy model generates is downloaded to local system, local system both can complete the optimization of local system according to the parameters downloaded, the parameters of download can be fed back to manufacturer again, data reference is provided to the production run of manufacturer, thus realize the lifting of entire new energy automobile performance.
The correlation parameter of described local vehicle, comprising: front position, distance travelled, the speed of a motor vehicle, throttle, brake, gear, turn to, motor speed, power of motor, Motor torque, electrokinetic cell total voltage, total current, single cell battery voltage, battery temperature, the internal resistance of cell, charging voltage or charging current.
Described vehicle optimized parameter comprises: vehicle acceleration, max. speed, the longest continual mileage, car weight, power consumption and ramp angle.
Described local system, comprising: entire car controller, electrokinetic cell, motor, electric machine controller, battery management system, charging set.
As shown in Figure 2, the single battery that battery enterprise produces, thousands of batteries is battery module by battery in groups factory in groups, after battery module assembling battery management system, uses electrokinetic cell by new-energy automobile producer.The application of the invention designed system, by the parameter such as series and parallel mode, battery total voltage, charging and discharging currents, battery case temperature, battery case size, battery vibration of analyzing and processing electrokinetic cell total voltage, total current, single cell battery voltage, battery temperature, the internal resistance of cell, electrokinetic cell, optimize battery model and battery gang mould shape parameter, for the design and use of battery enterprise, battery assembly plant, battery management system factory, factory of new forms of energy enterprise provide useful help.
When electrokinetic cell can not reach needing of new-energy automobile, the electrokinetic cell of replacing can be used the occasion not high to battery performance requirements such as energy storage, electric bicycle, low-speed electronic car.And the single battery of replacing power battery pack is present in performance difference, need again single battery consistent for performance to be screened in groups again, because designed system of the present invention has carried out omnidistance monitoring management to the single battery of power battery pack, by process and the excavation of large data, the consistent single battery of performance can be filtered out very easily carry out again in groups, save the cost of recycling and reusing of batteries.
By reference to the accompanying drawings the specific embodiment of the present invention is described although above-mentioned; but not limiting the scope of the invention; one of ordinary skill in the art should be understood that; on the basis of technical scheme of the present invention, those skilled in the art do not need to pay various amendment or distortion that creative work can make still within protection scope of the present invention.
Claims (10)
1., based on the New-energy electric vehicle vehicle performance elevator system of large data, it is characterized in that, comprising:
Local system, for power drive and the control of local vehicle, is uploaded to large data processing platform (DPP) by the correlation parameter of local vehicle by monitor network;
Monitor network, for being transferred to large data processing platform (DPP) by the correlation parameter of local vehicle by the mode of radio communication;
Large data processing platform (DPP), for carrying out Data classification, statistics, analysis, storage and excavation by the correlation parameter of vehicle;
Remote virtual system, for setting up vehicle, motor, the dummy model of battery and electric machine controller, using the input of the parameters after large data processing platform (DPP) process as dummy model, by setting up vehicle optimized parameter as output target, dummy model is optimized, the parameters that dummy model generates is downloaded to local system, local system both can complete the optimization of local system according to the parameters downloaded, the parameters of download can be fed back to manufacturer again, data reference is provided to the production run of manufacturer, thus realize the lifting of entire new energy automobile performance.
2., as claimed in claim 1 based on the New-energy electric vehicle vehicle performance elevator system of large data, it is characterized in that, described local system, comprising: entire car controller, electrokinetic cell, motor, electric machine controller, battery management system, charging set;
Described entire car controller, operation for realizing driver according to accelerator pedal position, gear, brake pedal force is intended to and all parts controlling car load carries out co-ordination, and entire car controller will speed up pedal position, braking force, gear information, steering wheel angle parameter send into monitor network;
Described electrokinetic cell is the energy source driving vehicle to travel;
Described motor is the driver driving vehicle to travel.
3., as claimed in claim 2 based on the New-energy electric vehicle vehicle performance elevator system of large data, it is characterized in that,
Described electric machine controller controls machine operation controller, electric machine controller by motor speed, moment of torsion, power, temperature, revolve varying signal, failure code parameter sends into monitor network;
Described battery management system, be detect, control, the control system that normally works of uniform power battery system, the parameters such as electrokinetic cell total voltage, total current, single cell battery voltage, battery temperature, the internal resistance of cell, balanced mode, euqalizing current are sent into monitor network by battery management system;
Described charging set is the controller of power battery charging, and charging voltage, charging current, charge mode are sent into monitor network by charging set.
4., as claimed in claim 1 based on the New-energy electric vehicle vehicle performance elevator system of large data, it is characterized in that,
Described monitor network, comprising: communication network in GPS, GPRS, 3G, 4G, WIFI telecommunications network and CAN, LIN, Flexray car, and monitor network is used for the data received from local system to pass to large data processing platform (DPP).
5., as claimed in claim 1 based on the New-energy electric vehicle vehicle performance elevator system of large data, it is characterized in that,
Described large data processing platform (DPP), comprising: cloud memory module, cloud administration module, large data processing module and data-mining module;
Described cloud memory module, for the storage of the associated parameter data of local vehicle, comprising: the write of database, access;
Described cloud administration module, for managing large data processing platform (DPP), comprising: the storage unit of cloud platform, the distribution of computational resource and management, user management;
Described large data processing module, for the conversion of the correlation parameter of local vehicle, grouping, tissue, calculating, retrieval, sequence;
Described data-mining module, for excavating important information in the data from large data processing module process; Described important information comprises by analyzing the total voltage of battery, total current, internal resistance, temperature information prediction battery life information, the like can excavate failure cause, electrical machinery life, the battery incipient fault information of motor.
6., as claimed in claim 1 based on the New-energy electric vehicle vehicle performance elevator system of large data, it is characterized in that,
Described remote virtual system, comprising: car load allocation models, battery be model, motor model, Electric Machine Control model, battery model, charging strategy model in groups;
Described car load allocation models, using complete vehicle quality, max. speed, maximum acceleration, course continuation mileage, maximumly to turn to, maximum climbing parameter as known quantity as input, the configuration parameter of the electrokinetic cell needed for calculating, drive motor, braking energy feedback strategy, brake system and charging set;
Described battery model in groups, using the series and parallel mode of battery, single battery quantity, single battery nominal voltage, battery arrangement mode as known quantity as input, using battery total voltage, battery single-unit voltage, single battery internal resistance, charging and discharging currents, euqalizing current, battery case temperature, battery vibration as dynamically measuring as input, predict the incipient fault after battery in groups and life-span.
7., as claimed in claim 6 based on the New-energy electric vehicle vehicle performance elevator system of large data, it is characterized in that,
Described motor model, using the design parameter of motor as known input quantity, using motor internal electric current, voltage, power and torque as dynamic input quantity, calculates the efficiency of motor, the incipient fault of pre-measured motor and life-span;
Described Electric Machine Control model, for simulated machine control strategy, by throttle signal, brake signal, revolves varying signal, dynamic battery voltage signal, motor temperature is as input, calculated by motor control strategy, calculate the PWM dutycycle of U/V/W three-phase voltage, realize the simulation of Electric Machine Control.
8., as claimed in claim 6 based on the New-energy electric vehicle vehicle performance elevator system of large data, it is characterized in that,
Described single battery model, using single battery voltage, battery ohmic internal resistance as input, sets up battery RC equivalent model, for analog simulation single battery dump energy and battery life;
Described charging strategy model, using externally fed voltage, current power battery total voltage, charging voltage, charging current as input, calculates the duration of charging, calculates the efficiency of charging strategy.
9., based on the New-energy electric vehicle vehicle performance method for improving of large data, it is characterized in that, comprise the steps:
Step (1): the entire car controller of local system, electric machine controller, battery manager, charging set realize interconnection by the internal bus of vehicle, local system by monitor network by the operational factor teletransmission of vehicle to large data processing platform (DPP);
Step (2): by large data processing and the large data mining of large data processing platform (DPP), revises and improves remote virtual system;
Step (3): by all kinds of parameter downloads perfect for remote virtual system correction to entire car controller, electric machine controller, battery manager, charging set, local controller and local system is optimized by real vehicle checking, if reach optimum index, terminate;
If do not reach optimum index, from step (1), carry out loop optimization, thus realize the closed-loop control promoting Full Vehicle System parameter;
If reach optimum index, then the battery group parameter of optimization, the parameter of electric machine, battery parameter are fed back to parts producer, carry out the perfect of related components.
10., as claimed in claim 9 based on the New-energy electric vehicle vehicle performance method for improving of large data, it is characterized in that,
The step of described step (2) is:
Step (2-1): large data are carried out carry out classifying, store, add up, change, calculate and transmitting according to whole-car parameters, the parameter of electric machine, Motor control parameters, battery group parameter, battery parameter, charge parameter;
Step (2-2): whole-car parameters is inputted car load allocation models, the configuration parameter of the electrokinetic cell needed for calculating, drive motor, braking energy feedback strategy, brake system and charging set;
Step (2-3): the parameter of electric machine is inputted motor model, calculates the efficiency of motor, the incipient fault of prediction and calculation motor and life-span;
Step (2-4): Motor control parameters is inputted Electric Machine Control model, calculates the PWM dutycycle of U/V/W three-phase voltage;
Step (2-5): by battery group parameter input battery model in groups, prediction and calculation battery in groups after incipient fault and the life-span;
Step (2-6): by single battery parameters input battery model, prediction and calculation emulation single battery dump energy and battery life;
Step (2-7): charge parameter is inputted charging strategy model, calculates duration of charging and charge efficiency.
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