CN105128698A - Electric vehicle endurance control system - Google Patents
Electric vehicle endurance control system Download PDFInfo
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- CN105128698A CN105128698A CN201510533112.8A CN201510533112A CN105128698A CN 105128698 A CN105128698 A CN 105128698A CN 201510533112 A CN201510533112 A CN 201510533112A CN 105128698 A CN105128698 A CN 105128698A
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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
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/72—Electric energy management in electromobility
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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
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
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Abstract
The invention discloses an electric vehicle endurance control system. The electric vehicle endurance control system comprises a controller, an electric motor and a signal analyzer, and the electric motor, the controller and the signal analyzer are connected through a CAN bus; a control decision module is connected with a PID control module, and the PID control module and the control decision module are connected to a CAN bus connection module; the signal analyzer comprises a data acquisition module, a filtering calculation module, a resistance degree calculation module, a road network matching module, a tilt angle sensor, a gradient calculation module, the CAN bus connection module and a wireless communication module; the data acquisition module, the resistance degree calculation module and the road network matching module are connected with the CAN bus connection module, and the filtering calculation module is connected to the data acquisition module and the resistance degree calculation module. The electric vehicle endurance control system can effectively prolong the endurance mileage of an electric vehicle.
Description
Technical field
The present invention relates to electronlmobil field, particularly relate to a kind of electronlmobil continuation of the journey control system.
Background technology
Present electronlmobil is more and more universal, but battery durable problem is the maximum obstruction met with in electronlmobil popularization, is also that domestic electric vehicle engineering difficulty has large breakthrough.Electronlmobil has a set of controller controlled the mode of operation of electrical motor, this controller be according to driver trample footfeed operation and control electrical motor rotate speed.And storage battery is the propulsion source that electrical motor rotates, but the voltage attenuation of storage battery is that when storage battery is full of electricity, voltage slowly reduces, and after the electric quantity consumption part of storage battery, voltage attenuation is more and more faster in nonlinear.Course continuation mileage is the important symbol weighing electric vehicle performance, and the battery-charging station of electronlmobil is not popularized, and the course continuation mileage therefore how extending electronlmobil just becomes the problem that everybody needs solution badly.
Summary of the invention
For solving the problems of the technologies described above, the invention provides a kind of electronlmobil continuation of the journey control system, for extending the course continuation mileage of electronlmobil.
The present invention is achieved in that
A kind of electronlmobil continuation of the journey control system, comprise controller, electrical motor and signal analyzer, described electrical motor, controller, signal analyzer are connected by CAN;
Described controller comprises pid control module, control decision module and CAN link block, and control decision module is connected with pid control module, and pid control module and control decision module are connected to CAN link block;
Signal analyzer comprises data acquisition module, filtering computing module, resistance degree computing module, road network module, obliquity sensor, gradient computing module, CAN link block and wireless communication module;
Data acquisition module, resistance degree computing module, road network module are connected with CAN link block respectively, filtering computing module is connected to data acquisition module and resistance degree computing module, described road network module comprises local Traffic network database, locating module and MEMS sensor, and described obliquity sensor, locating module, data acquisition module and MEMS sensor are connected to gradient computing module;
Data acquisition module is for gathering real-time vehicle signal from CAN;
Filtering computing module comprises velocity filtter, acceleration/accel filter and moment of torsion filter, and filtering computing module is used for carrying out filtering to the signals of vehicles of data collecting module collected;
Resistance degree computing module is used for resistance when travelling according to the output data calculating vehicle of filtering computing module;
Road network module for using Kalman Filter Technology, and carries out real-time line matching tracking in conjunction with the data of locating module, this Traffic network database and MEMS sensor;
Gradient computing module is used for the gradient calculating vehicle travel according to the detection data of obliquity sensor, locating module, vehicle power data and MEMS sensor, and by wireless communication module, the Gradient calculated is sent to server.
Further, the resistance when vehicle that described resistance degree computing module calculates travels sends to control decision module by CAN, and whether control decision module opens according to described resistance decision-making or close Energy Saving Control.
Further, described filtering computing module carries out filtering, difference, again filtering operation to the signals of vehicles that data acquisition module collects; In the filtering step, filtering computing module uses Digital Signal Processing to carry out power Spectral Estimation to described signals of vehicles, obtains the cutoff frequency of signals of vehicles, and carries out filtering by setting filtering type and filter order, obtains smooth curve signal.
Further, described road network module according to numerical map and positioning signal location technology, and in conjunction with the bearing data that MEMS sensor detects, improves path adaptation precision.
Further, the signals of vehicles of described data collecting module collected comprises the speed of a motor vehicle, rotating speed, moment of torsion.
Further, described pid control module calculates the difference e (t) of motor speed controlling valu r (t) of expection and actual output speed c (t) of electrical motor, the ratio (P) of described difference e (t), integration (I) and differential (D) are obtained controlling quantity by linear combination, and control electrical motor according to the controlling quantity obtained, make the actual speed c (t) of electrical motor close to motor speed controlling valu r (t).When Tuning PID Controller parameter, can according to the parameter of controller and the qualitative relationships between dynamic performance and steady-state behaviour.In order to reduce the parameter needing to adjust, first PI controller can be adopted.In order to ensure the safety of system, should arrange relatively more conservative parameter when debugging and starting, such as proportionality coefficient is not too big, and integration time is too not little, to avoid the abnormal condition occurring that system is unstable or overshoot is excessive.Provide a Step reference signal, the information of system performance can be obtained according to the output wave shape of controlled volume, such as overshoot and regulating time.According to the relation of pid parameter and system performance, should repeatedly regulate the parameter of PID.If the overshoot of step response is too large, could to stablize or unstable through multiple oscillation, proportionality coefficient, increase integration time should be reduced.If step response does not have overshoot, but controlled volume rises too slow, and settling time is oversize, should by contrary direction adjustment parameter.If the speed eliminating error is comparatively slow, suitably can reduces integration time, strengthen integral action.Repeatedly regulate proportionality coefficient and integration time, if overshoot is still comparatively large, can add differential and control, derivative time increases gradually from 0, repeatedly the ratio of adjustment control, the parameter of integration and differentiation part.
Further, whether described control decision module opens according to the speed of vehicle, the decision-making of resistance degree or closes Energy Saving Control;
The condition that Energy Saving Control starts is:
(1) 40km/h< car speed <120km/h, and
(2) resistance degree absolute value < setting threshold;
Energy Saving Control stop condition:
(1) resistance degree absolute value > setting threshold;
(2) when brake driver signal being detected; Or
(3) when driver's accelerator open degree rate of change exceedes threshold value.
Further, described control decision module also calculates for carrying out traveling power consumption economic zone, control decision module store measure obtain under unloaded, semi-load and fully laden, moment of torsion delivery curve during vehicle smooth-ride, moment of torsion delivery curve is divided into multiple continuous print speed interval, and according to current wagon control goal pace, control motor speed, make vehicle with speeds the most energy-conservation in present speed interval.
Beneficial effect of the present invention is: electronlmobil continuation of the journey control system of the present invention comprises electrical motor, controller, signal analyzer, controller comprises pid control module, control decision module and CAN link block, and signal analyzer comprises data acquisition module, filtering computing module, resistance degree computing module, road network module, obliquity sensor, gradient computing module, CAN link block and wireless communication module; The present invention controls in conjunction with road network calculating, signal filtering, Energy Saving Control, gradient calculating, PID and travels control technology between economic zone, substantially prolongs the course continuation mileage of electronlmobil.
Accompanying drawing explanation
Fig. 1 is the module frame chart of embodiment of the present invention electronlmobil continuation of the journey control system;
Fig. 2 is the signals of vehicles in embodiment of the present invention before filtering;
The signal that Fig. 3 obtains after filtration module filtering for signals of vehicles shown in Fig. 2;
Fig. 4 is the principle schematic of pid control module;
Vehicle load characteristic when Fig. 5 is flat pavement running.
Detailed description of the invention
By describing technology contents of the present invention, structural attitude in detail, realized object and effect, accompanying drawing is coordinated to be explained in detail below in conjunction with embodiment.
Refer to Fig. 1, electronlmobil continuation of the journey control system of the present invention comprises controller, electrical motor and signal analyzer, and described electrical motor, controller, signal analyzer are connected by CAN;
Described controller comprises pid control module, control decision module and CAN link block, and control decision module is connected with pid control module, and pid control module and control decision module are connected to CAN link block;
Signal analyzer comprises data acquisition module, filtering computing module, resistance degree computing module, road network module, obliquity sensor, gradient computing module, CAN link block and wireless communication module (i.e. 2G, 3G module in figure);
Data acquisition module, resistance degree computing module, road network module are connected with CAN link block respectively, filtering computing module is connected to data acquisition module and resistance degree computing module, described road network module comprises local Traffic network database, locating module and MEMS sensor, and described obliquity sensor, locating module, data acquisition module and MEMS sensor are connected to gradient computing module.
The function of each module of electronlmobil continuation of the journey control system refers to table one:
Table one
One, signal analyzer implementation:
Resistance degree calculates
Resistance degree calculates for decision-making when starting energy-saving controls, and when needs to close Energy Saving Control.Under automobile is in smooth-ride state, starting energy-saving controls, and stablizes at motoring condition, the control battery output therefore can try one's best many and do not affect the operation of driver; Closing opportunity of Energy Saving Control is: 1, be in the gradient moment, at this time driver often needs to downshift and draws high rotary speed to ensure the upward slope moment of vehicle, if carry out Energy Saving Control can navigate that vehicle driving up is unable even cannot go up a slope; 2, brake the moment, now need, by the completely leading power system of driver, additionally to intervene otherwise can safety problem be caused; 3, the idling descending moment, now power saving on the contrary is additionally controlled.
Vehicle drag degree defines, and refers to that automobile zero load is not having the acceleration/accel of straight-line travelling and the difference of automobile actual acceleration in resistance (not having rolling, the gradient, skid resistance, air resistance and other resistance) situation.The effect of vehicle drag degree is can concentrated expression integrated car load weight, road grade and resistance to motion, can carry out energy saving motor control according to vehicle drag degree.
Filtering calculates
In resistance degree computing module, the speed used, acceleration/accel, torque signal all need to carry out filtering process.Because the output shaft of automobile has tachogen usually, if the tach signal that can be collected easily is converted into the speed of a motor vehicle of automobile. to vehicle speed signal direct differential, although the acceleration/accel of automobile can be obtained, but because the acceleration signal noise obtained like this is very large, be difficult to the control system being applied to automobile.As shown in Figure 2, be original vehicle signal.Need the automobile longitudinal acceleration to vehicle speed signal carries out filtering, the method for difference, again filtering obtains good real-time and precision.Filtering algorithm module needs by digital signal processing algorithm, first carries out signals of vehicles power Spectral Estimation, obtains cutoff frequency, and design corresponding filtering type, filter order.Filter calculating essence is that the floating-point multiplication of a long sequence asks conjunction computing, therefore should be noted that the floating point operation ability of core processor when product design type selecting.Should be a smooth curve in ideal treatment effect situation after calculating.Be illustrated in figure 3 the signals of vehicles obtained after filtering calculates.In like manner, also need to carry out filtering process to signals such as moments of torsion, obtain the signal after processing and send into again in resistance degree computing module.
Map match calculates
Accurately can distinguish high speed, state's provincial highway, urban district, other road.This will relate to locating information and map matching technology, need to utilize map datum and some direction sensing amounts to realize high precision path adaptation.The correlation function that expection reaches project requires as follows:
(1) perpendicular to road error lower than 5% (i.e. path adaptation accuracy rate more than 95%).The difficulty that may exist can reach ideal effect to the process of parallel road.
(2) estimation and the maintenance of positioning signal inactive area site of road is realized.
The high precision matching feature of this respect needs by direction and acceleration pick-up, and fusion position location and map road network realize.Its concrete technology utilizes Kalman filtering, carries out data fusion, to realize high fix.Concrete blending algorithm also under study for action.
The geographical gradient calculates
Merge position location, obliquity sensor, automobile power DATA REASONING road grade, follow the method according to automobile power DATA REASONING road grade as follows at present:
The vehicle electric motor gross horsepower Pe at the uniform velocity travelled consumes: rolling resistance consumed power Pf; Grade resistance consumed power Pi; Windage consumed power Pw.Other: air-conditioning and vehicle mounted electrical apparatus wasted work rate Pk.Because air-conditioning and appliance power consumption hinder less relative to rolling resistance, windage, slope, therefore affect when vehicle travels principal element can temporarily ignore in consideration, during constant-speed driving, rating formula principle is as follows:
By formulae discovery automobile at the uniform velocity smooth-ride time changed power.Wherein G=mg is gravity, and f is surface friction coefficient (or claiming coefficient of rolling resistance), and ua is present speed, and CD is air resistance coefficient, and A is vehicle wind area, η
tfor mechanical efficiency of power transmission.From a shorter time window, the rolling resistance of the automobile at the uniform velocity travelled, windage, air-conditioning consumed power approximately constant, and total power consumption depends primarily on road grade size.
Under real world conditions, can not remain and at the uniform velocity travel by a car.Therefore need the running data of many vehicles to excavate, through the at the uniform velocity fragment of stretch line, excavate the slope change curve of whole circuit from each car.Again according to data cleansing, the poly-slope change curve excavating whole section of overall fusion step.
The data retained after data cleansing are that all vehicles are similar to the fragment at the uniform velocity travelled, the object done like this gets rid of acceleration/accel to the impact of changed power, and due at the uniform velocity fragment the speed mass conservation of vehicle therefore road friction resistance consumed power is equal, windage consumed power is approximately equal, such power of vehicle change mainly affects by gradient factor.
The present invention only to the demarcation carrying out load-carrying and power consumption as initial reference Segment A car, and need not need the concrete load-carrying data of other vehicle, can estimate to merge by data cleansing and centre data the slope change data obtaining whole section.
Therefore select to need to demarcate A car during initial reference fragment, this is also easily realize (such as carry out weight demarcation to A car, or allow the unloaded load-carrying of A car be exactly standard complete vehicle quality) in actual development project process.The anti-relative slope change sequence that pushes away of the traveling power consumption of calibration vehicle on level road is utilized to be absolute slope change sequence, utilize the car cluster center of big data quantity, in conjunction with some calibration measurements, expectation can carry out large-scale geographical gradient environment measurement, sets up complete geographical Gradient storehouse.
Two, controller actualizing technology
PID controls
In actual motor controls, in order to the requirement making vehicle electric motor reach speed of a motor vehicle control, need to carry out dynamic PID control according to practical operation situation and the difference controlling to expect, PID controls to be a kind of more common control method, in the industry such as metallurgy, machinery, chemical industry, obtain widespread use.Regulatory PID control system principle diagram as shown in Figure 4.
Control system is made up of analog pid controller and controlled object, PID controller is a kind of linear controller, and the motor speed controlling valu that namely it expect according to given value r (t) and the namely actual tachometer value of real output value c (t) form controller excursion
e(t)＝r(t)-c(t)
The ratio (P) of deviation, integration (I) and differential (D) are formed controlling quantity by linear combination, controlled object is controlled, make actual result constantly control result to expection close, therefore claim PID controller.
The decision-making of Energy Saving Control on off control
Energy Saving Control entry condition is:
(1) 40km/h< car speed <120km/h, now thinks that automobile can smooth ride, meets starting energy-saving controlled condition.
(2) resistance degree absolute value < setting threshold, now thinks that environment residing for automobile is steady, without upward slope, descending, the anxious application conditions accelerated, meets starting energy-saving controlled condition.
Above two conditions must meet simultaneously, just can starting energy-saving controlling functions.
Energy Saving Control stop condition:
(1) resistance degree absolute value > setting threshold, now automobile may run into the extraordinary circumstances needing large power, as drawn high abrupt slope on rotating speed, or run into large resistance Expenditure Levels, as driver brakes, or run into negative resistance dynamics situation, during descending as long in vehicle, use electrical motor anti-dragged brake.
(2) when brake driver signal being detected.
(3) when driver's accelerator open degree rate of change exceedes threshold value.
Above three conditions meet one, namely will close energy-saving control function.
Economic interval computation
First the sky measuring institute's control vehicle is needed to be fully loaded with torque characteristics, as shown below, measure and obtain the moment of torsion delivery curve that automobile balance travels under sky, semi-load, fully laden:
When moment of torsion delivery curve refers to that a certain automobile travels with certain load, certain gear, certain gradient, electrical motor needs the M curve exported.Moment of torsion delivery curve example when Fig. 5 is flat pavement running.
Abscissa is motor speed, and ordinate is electric Driving Torque, and the Roman number such as I, II, III, IV, V, VI represents 1,2,3,4,5,6 grades of manual gear; Solid line is fully loaded moment of torsion delivery curve, and horizontal dotted line is moment of torsion delivery curves semi-load, and pecked line is unloading torque delivery curve.
Gear is certain, and motor speed is certain, if skidding does not appear in wheel, that speed of a motor vehicle is certain.Because the speed of a motor vehicle is that during vehicle travels, the topmost operation factors of driver is also the principal element determining running time, and the rate of fuel consumption parameter in the corresponding universal characteristic table of rotating speed, it is very important for therefore drawing speed of a motor vehicle rotating speed homologous thread to statistics fuel consumption of 100km and control automobile mode of operation.Their relation curve can be calculated when knowing Choosing of Main Gear Ration of The Motor Cars and transmitting ratio parameter, also drawing their relation curve by actual measurement.When micro-cruising, according to set velocity amplitude, on a minizone, speed is adjusted toward the most energy-conservation direction as far as possible.Simultaneously according to the change of resistance degree, the empty fully laden of real-time estimation vehicle, timely switch load curve, finds correct energy-conservation interval.
The present invention calculates the resistance degree of vehicle in traveling by described signal analyzer, record the road net data of Current vehicle simultaneously, locating module obtains the elements of a fix of Current vehicle, to be combined with MEMS sensor the accuracy improving and locate by locating module, road net data local according to elements of a fix coupling again, signal analyzer obtains the resistance degree in this section according to road network, controller is passed to by CAN, controller formulates control decision in conjunction with resistance degree and road network data, the rotating speed of electrical motor is controlled to adjust by PID, the finite energy that storage battery is provided is effectively utilized.
The local road net data of signal analyzer can obtain Data Update by wireless communication module from cloud server terminal.In addition, model analyzer can carry out gradient calculating according to CAN data acquisition module, obliquity sensor, locating module, MEMS sensor, is upgraded and improve the road net data of cloud server terminal by wireless communication module.
Signal analyzer passed through continuous autonomous learning, memory storage and accumulation optimization, the most energy-conservation drive manner can be searched out, the route on and off duty that such as car owner fixes to after the study in path, accumulation and analysis, provides the most energy-conservation a kind of driving control method by the signal analyzer of foregoing invention.Car owner takes this driving control method maloperation can be caused unnecessary electric energy to be used for the driving of longer time, extends the course continuation mileage of battery-driven car.
The foregoing is only embodiments of the invention; not thereby the scope of the claims of the present invention is limited; every utilize specification sheets of the present invention and accompanying drawing content to do equivalent structure or equivalent flow process conversion; or be directly or indirectly used in other relevant technical fields, be all in like manner included in scope of patent protection of the present invention.
Claims (8)
1. an electronlmobil continuation of the journey control system, it is characterized in that, comprise controller, electrical motor and signal analyzer, described electrical motor, controller, signal analyzer are connected by CAN;
Described controller comprises pid control module, control decision module and CAN link block, and control decision module is connected with pid control module, and pid control module and control decision module are connected to CAN link block;
Signal analyzer comprises data acquisition module, filtering computing module, resistance degree computing module, road network module, obliquity sensor, gradient computing module, CAN link block and wireless communication module;
Data acquisition module, resistance degree computing module, road network module are connected with CAN link block respectively, filtering computing module is connected to data acquisition module and resistance degree computing module, described road network module comprises local Traffic network database, locating module and MEMS sensor, and described obliquity sensor, locating module, data acquisition module and MEMS sensor are connected to gradient computing module;
Data acquisition module is for gathering real-time vehicle signal from CAN;
Filtering computing module comprises velocity filtter, acceleration/accel filter and moment of torsion filter, and filtering computing module is used for carrying out filtering to the signals of vehicles of data collecting module collected;
Resistance degree computing module is used for resistance when travelling according to the output data calculating vehicle of filtering computing module;
Road network module for using Kalman Filter Technology, and carries out real-time line matching tracking in conjunction with the data of locating module, this Traffic network database and MEMS sensor;
Gradient computing module is used for the gradient calculating vehicle travel according to the detection data of obliquity sensor, locating module, vehicle power data and MEMS sensor, and by wireless communication module, the Gradient calculated is sent to server.
2. electronlmobil continuation of the journey control system according to claim 1, it is characterized in that, the resistance when vehicle that described resistance degree computing module calculates travels sends to control decision module by CAN, and whether control decision module opens according to described resistance decision-making or close Energy Saving Control.
3. electronlmobil continuation of the journey control system according to claim 1, it is characterized in that, described filtering computing module carries out filtering, difference, again filtering operation to the signals of vehicles that data acquisition module collects; In the filtering step, filtering computing module uses Digital Signal Processing to carry out power Spectral Estimation to described signals of vehicles, obtains the cutoff frequency of signals of vehicles, and carries out filtering by setting filtering type and filter order, obtains smooth curve signal.
4. electronlmobil continuation of the journey control system according to claim 1, is characterized in that, described road network module according to numerical map and positioning signal location technology, and in conjunction with the bearing data that MEMS sensor detects, improves path adaptation precision.
5. electronlmobil continuation of the journey control system according to claim 1, it is characterized in that, the signals of vehicles of described data collecting module collected comprises the speed of a motor vehicle, rotating speed, moment of torsion.
6. electronlmobil continuation of the journey control system according to claim 1, it is characterized in that, described pid control module calculates the difference e (t) of motor speed controlling valu r (t) of expection and actual output speed c (t) of electrical motor, the ratio (P) of described difference e (t), integration (I) and differential (D) are obtained controlling quantity by linear combination, and control electrical motor according to the controlling quantity obtained, make the actual speed c (t) of electrical motor close to motor speed controlling valu r (t).
7. electronlmobil according to claim 1 continuation of the journey control system, is characterized in that, whether described control decision module opens according to the speed of vehicle, the decision-making of resistance degree or close Energy Saving Control;
The condition that Energy Saving Control starts is:
(1) 40km/h< car speed <120km/h, and
(2) resistance degree absolute value < setting threshold;
Energy Saving Control stop condition:
(1) resistance degree absolute value > setting threshold;
(2) when brake driver signal being detected; Or
(3) when driver's accelerator open degree rate of change exceedes threshold value.
8. electronlmobil continuation of the journey control system according to claim 1, it is characterized in that, described control decision module also calculates for carrying out traveling power consumption economic zone, control decision module store measure obtain under unloaded, semi-load and fully laden, moment of torsion delivery curve during vehicle smooth-ride, moment of torsion delivery curve is divided into multiple continuous print speed interval, and according to current wagon control goal pace, control motor speed, make vehicle with speeds the most energy-conservation in present speed interval.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107808427A (en) * | 2017-09-28 | 2018-03-16 | 航天科技控股集团股份有限公司 | A kind of car data statistical method based on CAN |
| CN108860151A (en) * | 2018-07-10 | 2018-11-23 | 江西凯马百路佳客车有限公司 | A kind of pure electric car drive system energy-saving control method |
| CN109100160A (en) * | 2018-09-25 | 2018-12-28 | 安徽江淮汽车集团股份有限公司 | Method for controlling driving speed and system for the test of electric car course continuation mileage |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050274553A1 (en) * | 2004-06-09 | 2005-12-15 | Salman Mutasim A | Predictive energy management system for hybrid electric vehicles |
| JP2010167964A (en) * | 2009-01-23 | 2010-08-05 | Nissan Motor Co Ltd | Control device and control method for hybrid vehicle |
| CN102765388A (en) * | 2012-07-03 | 2012-11-07 | 清华大学 | Vehicle control method based on multi-information integration |
| CN102991375A (en) * | 2012-12-10 | 2013-03-27 | 齐宪东 | Electric vehicle controller |
| CN104300648A (en) * | 2014-11-04 | 2015-01-21 | 徐叶 | Electric vehicle running control system |
| CN104691363A (en) * | 2015-03-26 | 2015-06-10 | 严振华 | Electric bicycle mechanical variable speed type motor controller and variable speed control method thereof |
-
2015
- 2015-08-27 CN CN201510533112.8A patent/CN105128698B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050274553A1 (en) * | 2004-06-09 | 2005-12-15 | Salman Mutasim A | Predictive energy management system for hybrid electric vehicles |
| JP2010167964A (en) * | 2009-01-23 | 2010-08-05 | Nissan Motor Co Ltd | Control device and control method for hybrid vehicle |
| CN102765388A (en) * | 2012-07-03 | 2012-11-07 | 清华大学 | Vehicle control method based on multi-information integration |
| CN102991375A (en) * | 2012-12-10 | 2013-03-27 | 齐宪东 | Electric vehicle controller |
| CN104300648A (en) * | 2014-11-04 | 2015-01-21 | 徐叶 | Electric vehicle running control system |
| CN104691363A (en) * | 2015-03-26 | 2015-06-10 | 严振华 | Electric bicycle mechanical variable speed type motor controller and variable speed control method thereof |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107808427A (en) * | 2017-09-28 | 2018-03-16 | 航天科技控股集团股份有限公司 | A kind of car data statistical method based on CAN |
| CN108860151A (en) * | 2018-07-10 | 2018-11-23 | 江西凯马百路佳客车有限公司 | A kind of pure electric car drive system energy-saving control method |
| CN109100160A (en) * | 2018-09-25 | 2018-12-28 | 安徽江淮汽车集团股份有限公司 | Method for controlling driving speed and system for the test of electric car course continuation mileage |
| CN109100160B (en) * | 2018-09-25 | 2020-05-29 | 安徽江淮汽车集团股份有限公司 | Vehicle speed control method and system for electric vehicle endurance mileage test |
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