CN102407850B - Hybrid electric bus energy management method based on random operation condition model - Google Patents

Hybrid electric bus energy management method based on random operation condition model Download PDF

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CN102407850B
CN102407850B CN2011102878322A CN201110287832A CN102407850B CN 102407850 B CN102407850 B CN 102407850B CN 2011102878322 A CN2011102878322 A CN 2011102878322A CN 201110287832 A CN201110287832 A CN 201110287832A CN 102407850 B CN102407850 B CN 102407850B
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speed
displacement
historical
power
motor vehicle
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CN102407850A (en
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宋春跃
潘正
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Zhejiang University ZJU
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Abstract

The invention discloses a hybrid electric bus energy management method based on a random operation condition model. The method comprises the following implementation steps of: 1) obtaining a historical speed-displacement relationship and an acceleration-displacement relationship according to the historical speed of the bus, obtaining the historical average speed and average acceleration on each displacement point on the running path, and obtaining a speed random factor of the bus on each displacement point according to the variance of the historical speed; 2) obtaining the power need within a certain prediction displacement section after the current displacement point, obtaining a historical motor power change range within the certain prediction displacement section after the current displacement point of the bus, and obtaining a power distribution ratio range of the current displacement point; and 3) obtaining the optimal distribution ratio of hybrid power, and controlling the output states of an engine and a motor according to the optimal distribution ratio. The method disclosed by the invention has the advantages of reasonable energy distribution, good fuel economy, little exhaust emission, good robustness, energy conservation and environmental friendliness.

Description

Hybrid-power bus energy management method based on the random walk condition model
Technical field
The present invention relates to hybrid power management control technique field, be specifically related to a kind of hybrid-power bus energy management method.
Background technology
On the earth, the discharging due to fuel-engined vehicle causes problem of environmental pollution day by day serious at present, and oil resources are limited, just may exploit after decades.Therefore, hybrid vehicle (HEV) becomes the study hotspot of automotive field, HEV adopts at least two kinds of propulsions source, therefore in order to allow as much as possible engine operation interval in best effort, reach purposes such as reducing fuel oil consumption, minimizing pollutant emission, recycling braking kinetic energy.
City bus has a fairly large number of characteristics as city main traffic instrument, and is larger for the pollution effect of urban air, so people begin to reduce the aerial contamination in city at city bus field interpolation Technology of Hybrid Electric Vehicle.Many seminars have been arranged at present at the energy management strategy of research hybrid-power bus, however the specific aim of most of control policies a little less than, do not consider the operation characteristic of every circuit, the control effect that obtains like this is not very good.Some seminars utilize the sample that GPS records to predict the bus characteristics of motion in future.And formulate the energy management strategy with this by means such as dynamic programmings, this way can utilize state of cyclic operation to estimate the power demand of each time period well, reaches the purpose of global optimization.Yet this strategy does not have universality, just can reach the control effect when only having bus to operate according to the model track definitely.But the operation that actual conditions are buses has very strong randomness, the path motion in the time of hardly can be according to custom strategies, and each consuming time be also different, if control policy probably can't reach the control effect of expection based on fixed model.
Summary of the invention
The technical problem to be solved in the present invention is to provide that a kind of energy distributes rationally, fuel economy is high, exhaust emissions is few, robustness is good, the hybrid-power bus energy management method based on the random walk condition model of energy-conserving and environment-protective.
For solving the problems of the technologies described above, the technical solution used in the present invention is: a kind of hybrid-power bus energy management method based on the random walk condition model, and implementation step is as follows:
1) carry out according to the historical speed of a motor vehicle of bus running the historical speed of a motor vehicle-displacement relation that integration obtains bus; Carry out diff according to the historical speed of a motor vehicle of bus running and obtain acceleration/accel-displacement relation; According to the speed of a motor vehicle-displacement relation and the acceleration/accel-displacement relation of each group history, obtain historical average ground speed and the average acceleration of each displacement point on running route, obtain bus at the speed of a motor vehicle random factor of each displacement point according to the variance of the historical speed of a motor vehicle;
2) obtain the power demand in certain predictive displacement section after current displacement point according to historical average ground speed and average acceleration, obtain bus historical motor power variation range in certain predictive displacement section after current displacement point according to speed of a motor vehicle random factor simultaneously, obtain the power-division ratios scope of current displacement point according to certain predictive displacement section internal power demand and historical motor power variation range after current displacement point;
3) with power-division ratios scope combined objective function J = min u E { ∫ S 0 S 0 + P ( w f J f ( u , s ) + w g J g ( u , s ) ) ds } Enumerate the Optimal Ratio that obtains hybrid power, and according to the output state of Optimal Ratio control engine and motor, wherein J fBe the fuel consumption rate of bus engine, J gBe the pollutant emission rate of bus engine, w fFor setting fuel oil consumption weights, w gFor setting the pollutant emission weights, s is the displacement of current displacement point, and E is the operational symbol of averaging, and P is the later predictive displacement point quantity of current displacement point, and u is the power-division ratios sampling value in the power-division ratios scope.
As further improvement in the technical proposal of the present invention:
Described step 1) in advance the running route of bus is divided into a plurality of sub-highway sections, described step 3 according to website in) in the displacement of current displacement point refer to the displacement of current displacement point relatively current sub-highway section start position.
3, the hybrid-power bus energy management method based on the random walk condition model according to claim 2, it is characterized in that, described step 1) carrying out according to the historical speed of a motor vehicle record of bus running the concrete steps that integration obtains the historical speed of a motor vehicle-displacement relation of bus in comprises: excursion that will every individual sub-highway section is divided into the N segment according to the time, then to every a bit of basis
∫ t i t i + 1 V ( t ) dt = 1 2 ( t i + 1 - t i ) ( V ( t i ) + V ( t i + 1 ) ) + R
Carry out integration and obtain every a bit of displacement, wherein t iBe the zero hour of i segment, t i+1Be the zero hour of i+1 segment, V (t i) be t iThe speed of a motor vehicle constantly, R is truncated error; Then every a bit of displacement summation is obtained the excursion of bus in current sub-highway section, obtain the historical speed of a motor vehicle-displacement relation of bus according to the historical speed of excursion and current location.
described step 1) organize the historical speed of a motor vehicle-displacement relation and acceleration/accel-displacement relation according to each in, obtain that on running route, historical average ground speed and the average acceleration of each displacement point specifically refers to, obtain the crossing in current sub-highway section, if a plurality of crossings are arranged in current highway section choose one of them main crossing according to the comentropy index, the historical speed of a motor vehicle-displacement relation in this zone, crossing of young pathbreaker large according to the historical speed of a motor vehicle is categorized as red light data acquisition and green light data acquisition, then red light data acquisition and green light data acquisition are asked for respectively its historical average ground speed and obtained average acceleration.
Described step 1) organize the historical speed of a motor vehicle-displacement relation and acceleration/accel-displacement relation according to each in, obtain that on running route, historical average ground speed and the average acceleration of each displacement point refers to: will choose fixing motion vector according to setting step-length, then search two nearest sampling points that are used for obtaining the historical speed of a motor vehicle of the current displacement point of distance, then utilize interpolation arithmetic to obtain the speed of a motor vehicle and the acceleration/accel of current displacement point, and calculate and respectively organize historical data in historical average ground speed and the average acceleration of this displacement point.
Described step 2) obtaining bus power of motor variation range in certain predictive displacement section after current displacement point according to speed of a motor vehicle random factor in specifically refers to:
A) obtain the speed of a motor vehicle regularity of distribution of every bit in predictive displacement point according to speed of a motor vehicle random factor
Figure BDA0000094335450000024
Be s i+1The historical average ground speed of displacement point;
B) speed of a motor vehicle regularity of distribution satisfies constraint condition P ( v i + 1 ≥ 2 I ( s i + 1 - s i ) Q ( SOC _ Init - SOC _ Low ) - v i ) ≥ α Obtain the variation range that current of electric I allows, wherein s iBe i displacement point, s i+1Be i+1 displacement point, Q is the total capacitance of storage battery, and SOC_Init is the initial state-of-charge that storage battery is positioned at current displacement point, and SOC_Low is the lower limit of storage battery charge state, and α is the conservative parameter of the battery discharging of setting;
C) basis Obtain power of motor P emThe historical variations scope, U wherein 0Be storage battery open-loop voltage, R iBe internal resistance.
Described step 3) in, power-division ratios scope combined objective function being enumerated the Optimal Ratio that obtains hybrid power specifically refers to: the power-division ratios scope is carried out Interval Discrete, with the end points of Interval Discrete and the Along ent value power-division ratios as sampling, the described objective function of each power-division ratios difference substitution with sampling obtains the power division that meets objective function and is compared to Optimal Ratio.
the present invention has following advantage: the historical speed of a motor vehicle-displacement relation that the present invention is based on statistics obtains the power demand of current displacement point and the power-division ratios scope that the power of motor variation range is obtained current displacement point, and then by enumerate the Optimal Ratio that obtains hybrid power according to objective function, and according to the output state of Optimal Ratio control engine and motor, combine fuel oil and the discharging parameter of vehicle motor, the statistical information of the historical speed of a motor vehicle, the uncertain information of having considered the speed of a motor vehicle is arranged, limit distribution ratio by uncertain information, make the boundary crossing probability of state-of-charge reduce, can not only promote fuel economy, and the chance that charge capacity crosses the border is controlled in the acceptable scope of user, random process for the actual vehicle operation has good robustness, having the energy distributes rationally, fuel economy is high, exhaust emissions is few, robustness is good, the advantage of energy-conserving and environment-protective.
Description of drawings
Fig. 1 is the implementing procedure schematic diagram of the embodiment of the present invention.
Fig. 2 is the framed structure schematic diagram of the embodiment of the present invention.
Fig. 3 is embodiment of the present invention step 1) obtain the schematic flow sheet of speed of a motor vehicle random factor.
Fig. 4 is embodiment of the present invention step 3) schematic flow sheet.
The specific embodiment
As shown in Figure 1, the embodiment of the present invention is as follows based on the implementation step of the hybrid-power bus energy management method of random walk condition model:
1) carry out according to the historical speed of a motor vehicle of bus running the historical speed of a motor vehicle-displacement relation that integration obtains bus; Carry out diff according to the historical speed of a motor vehicle of bus running and obtain acceleration/accel-displacement relation; According to the speed of a motor vehicle-displacement relation and the acceleration/accel-displacement relation of each group history, obtain historical average ground speed and the average acceleration of each displacement point on running route, obtain bus at the speed of a motor vehicle random factor of each displacement point according to the variance of the historical speed of a motor vehicle;
2) obtain the power demand of each position in estimation range according to historical average ground speed and average acceleration, simultaneously according to speed of a motor vehicle random factor obtain bus each position allow in estimation range the power of motor variation range, the power-division ratios scope of obtaining each position in estimation range according to power demand and the power of motor variation range of predictive displacement point;
3) according to objective function J = min u E { ∫ S 0 S 0 + P ( w f J f ( u , s ) + w g J g ( u , s ) ) ds } Enumerate the Optimal Ratio that obtains hybrid power, and according to the output state of Optimal Ratio control engine and motor, wherein J fBe the fuel consumption rate of bus engine, J gBe the pollutant emission rate of bus engine, w fFor setting fuel oil consumption weights, w gFor setting the pollutant emission weights, s is the displacement of current displacement point, and E is the operational symbol of averaging, and P is the quantity of predictive displacement point, and u is the power-division ratios sampling value in the power-division ratios scope.In the present embodiment, Optimal Ratio is with u *Express Optimal Ratio u *Obtain by enumeration methodology, namely at one group of power-division ratios u of power-division ratios scope sampling, u substitution objective function is calculated, the power-division ratios u of result of calculation value minimum is Optimal Ratio u *
The present embodiment step 1) in advance the running route of bus is divided into a plurality of sub-highway sections, step 3 according to website in) in the displacement of current displacement point refer to the displacement of current displacement point relatively current sub-highway section start position.Step 1) obtain bus in after the speed of a motor vehicle random factor of each displacement point, speed of a motor vehicle model can be expressed as the stack model of V (S)=E (S)+w (S), wherein V (S) is the model speed of a motor vehicle, E (S) is historical average ground speed, w (S) is speed of a motor vehicle random factor, the regularity of distribution that w (S) is satisfied is N (0, σ (S)), and wherein σ (S) is the historical speed variance of each displacement point.
As shown in Figure 2, the hardware configuration of the embodiment of the present invention mainly comprises microprocessor, GPS module and read-out, wherein microprocessor employing model is the arm processor realization of S3C2440, read-out adopts liquid crystal display to realize, microprocessor is provided with a GPIO port, the information exchange that arrives at a station is crossed GPIO port input microprocessor, and microprocessor triggers the judgement current sub-highway section that is according to the signal of input, and calls respectively data model that should sub-highway section.Move the WINCE system on microprocessor, due to this chip block of the S3C2440 that uses after having determined on hardware that WINCE starts, application program can't directly be accessed physical address, its former because this chip block will be accessed peripheral hardware and just must set up mapping relations between physical memory and virtual memory with the MMU unit in application program.The WINCE system comprises serial port drive program element and GPIO drive program unit, and the meaning of serial port drive program element is can access peripheral hardware based on the application program of WinCE, reads data log from the internal memory of GPS module in order to realize; The effect of GPIO drive program unit is to introduce number control signal, and realization with the gps data segmentation, can be configured to interrupt pin take the station as waypoint with a universal I/O port.The software that the exploitation of above-mentioned drive program need to be used is Platform Builder.After realizing each interface function, also must make a little suitable modifications in platform.bib and platform.reg file, driving could successfully be added in the WinCE reflection and when start and load like this.Mainly do the Data Integration work for the treatment of in the application program aspect, software used is EVC.Need first to install the self-defined platform SDK that is derived by Platform Builder before exploitation.Utilize serial port drive to read gps data in application program, open up simultaneously the interrupt signal of a thread waits GPIO mouth, in case interruption that the signal that arrives at a station causes is arranged just with data sectional.Obtain bus after the speed of a motor vehicle of each moment correspondence of each highway section, in application program, data are done further processing.
The present embodiment step 1) carrying out according to the historical speed of a motor vehicle record of bus running the concrete steps that integration obtains the historical speed of a motor vehicle-displacement relation of bus in comprises: excursion that will every individual sub-highway section is divided into the N segment according to the time, then to every a bit of basis
∫ t i t i + 1 V ( t ) dt = 1 2 ( t i + 1 - t i ) ( V ( t i ) + V ( t i + 1 ) ) + R
Carry out integration and obtain every a bit of displacement, wherein t iBe the zero hour of i segment, t i+1Be the zero hour of i+1 segment, V (t i) be t iThe speed of a motor vehicle constantly, R is truncated error; Then every a bit of displacement summation is obtained the excursion of bus in current sub-highway section, obtain the historical speed of a motor vehicle-displacement relation of bus according to the historical speed of excursion and current location.Adopt trapezoidal method to calculate truncated error R in the present embodiment, the expression formula of the truncated error R of trapezoidal method is
R = - ( t i + 1 - t i ) 2 12 V ′ ′ ( ξ ) , ξ∈[t i，t i+1]
As seen the error exponent number by the said method integration is two powers of sampling time interval.At interval [t 0, t f] in, the excursion of vehicle can be used
∫ t 0 t f V ( t ) dt = Σ i = 1 N ∫ t i t i + 1 V ( t ) dt
Calculate, adopt numerical integration to ask displacement to have certain error, the length of same highway section in different samples is all different, yet for time quantum, the displacement in same highway section is more stable.
step 1) organize the historical speed of a motor vehicle-displacement relation and acceleration/accel-displacement relation according to each in, obtain that on running route, historical average ground speed and the average acceleration of each displacement point specifically refers to, obtain the crossing in current sub-highway section, if a plurality of crossings are arranged in current highway section choose one of them main crossing according to the comentropy index, the historical speed of a motor vehicle-displacement relation in this zone, crossing of young pathbreaker large according to the historical speed of a motor vehicle is categorized as red light data acquisition and green light data acquisition, then red light data acquisition and green light data acquisition are asked for respectively its historical average ground speed and obtained average acceleration.As shown in Figure 3, the first segmentation of the GPS module of the present embodiment receives gps data, be the relation of the speed of a motor vehicle and displacement with the transformation of the speed of a motor vehicle and time, choose main crossroads, and according to the traffic lights situation, the historical sample classification is obtained red light data acquisition and green light data acquisition, obtaining the speed of a motor vehicle of same displacement point according to interpolation, finally analyzing speed of a motor vehicle Changing Pattern and the speed of a motor vehicle random factor of this each displacement point of sub-highway section from historical speed of a motor vehicle sample.In the present embodiment, in the present embodiment, if the speed of a motor vehicle less than 5km/s, is judged as red light phase; Otherwise be judged to be green light phase, in view of running into the situation of a highway section Multiple Intersections when driving, can make like this model more complicated in indivedual highway sections, only consider for the purpose of simplifying the description a topmost crossing in the present embodiment, the method for choosing master is as follows: the parking probability P of at first adding up each crossing in current highway section i, then according to H i=-P ilog 2P i-(1-P i) log 2(1-P i) select one of them crossing regional.H iEssence be that the comentropy of two kinds of traffic lights is done weighted mean, its size has reflected total quantity of information that this crossing comprises.As seen the distribution of red light and green light situation is average, and quantity of information is just larger, the sort of long-term almost crossing of bright a kind of lamp, and classification is just almost meaningless.
The present embodiment step 1) organize the historical speed of a motor vehicle-displacement relation and acceleration/accel-displacement relation according to each in, obtain that on running route, historical average ground speed and the average acceleration of each displacement point specifically refers to: will choose fixing motion vector according to setting step-length, then search two nearest sampling points that are used for obtaining the historical speed of a motor vehicle of the current displacement point of distance, then utilize interpolation arithmetic to obtain the speed of a motor vehicle and the acceleration/accel of current displacement point, and calculate and respectively organize historical data in historical average ground speed and the average acceleration of this displacement point.In each historical sample, the discrete sampling point that gathers the speed of a motor vehicle is all different, in order to integrate the information of many group samples, must first obtain unified abscissa tolerance, the present embodiment is by the problem of fixed step size and interpolation arithmetic, effectively solve the problem of unified abscissa tolerance, thereby can conveniently realize obtaining the historical speed of a motor vehicle of displacement point, historical average ground speed and historical average acceleration.In the present embodiment, the step-length of motion vector is 10 meters, and interpolation arithmetic adopts the lagrange interpolation formula, and the lagrange interpolation formula is as follows:
y = x - x 1 x 0 - x 1 y 0 + x - x 0 x 1 - x 0 y 1
Wherein, (x 0, y 0) be position and the speed of a motor vehicle of a sampling point, (x 1, y 1) be position and the speed of a motor vehicle of another sampling point.So just obtain each historical sample in the speed of a motor vehicle at fixed displacement point place.
The power-division ratios that is met probability constraints by the information such as the speed of a motor vehicle of the SOC state of current displacement point, the speed of a motor vehicle, next position is interval.Also need check for this interval whether to make motor torque too low, further dwindle the feasible zone of power-division ratios.Then with Interval Discrete obtained above, only consider end points in the interval and the value at several Along ents places, closeer precision is got in the interval higher, but can increase computing time simultaneously.Adopt afterwards enumerative technique to attempt each possible power-division ratios, u of every selection just calculates next step SOC_Init, then next step is also calculated all possible power-division ratios as stated above, until P step estimation range finishes.Then calculate P step estimation range and apply pollutant emission and the oil consumption that obtains after above-mentioned power-division ratios sequence, and choose optimum power-division ratios sequence.Consider from the angle of the following operating condition of vehicle, can allow bus discharge and recharge in appropriate position, can increase oil consumption to battery charge, but the oil consumption that increases at diverse location is different, the opportunity of discharge is also very crucial, because the fuel-economy type at some position driving engine is very low, allow motor provide power-assisted can significantly reduce oil consumption in these positions.
The present embodiment step 2) obtaining bus power of motor variation range in certain predictive displacement section after current displacement point according to speed of a motor vehicle random factor in specifically refers to:
A) obtain the speed of a motor vehicle regularity of distribution of every bit in predictive displacement point according to speed of a motor vehicle random factor
Figure BDA0000094335450000071
Figure BDA0000094335450000072
Be s i+1The historical average ground speed of displacement point;
B) speed of a motor vehicle regularity of distribution satisfies constraint condition P ( v i + 1 ≥ 2 I ( s i + 1 - s i ) Q ( SOC _ Init - SOC _ Low ) - v i ) ≥ α Obtain the variation range that current of electric I allows, wherein s iBe i displacement point, s i+1Be i+1 displacement point, Q is the total capacitance of storage battery, and SOC_Init is the initial state-of-charge that storage battery is positioned at current displacement point, and SOC_Low is the lower limit of storage battery charge state, and α is the conservative parameter of the battery discharging of setting;
C) basis
Figure BDA0000094335450000074
Obtain power of motor P emThe variation range that allows, wherein U 0Be storage battery open-loop voltage, R iBe internal resistance.
Step 3) in, power-division ratios scope combined objective function being enumerated the Optimal Ratio that obtains hybrid power specifically refers to: the power-division ratios scope is carried out Interval Discrete, with the end points of Interval Discrete and the Along ent value power-division ratios as sampling, each power-division ratios difference substitution objective function with sampling obtains the power division that meets objective function and is compared to Optimal Ratio.Get final product to get the constant interval that allows of power-division ratios by the constraint condition of said motor power and total power demand; With Interval Discrete obtained above, only consider end points in the interval and the value at several Along ents places, closeer precision is got in the interval higher, but can increase computing time simultaneously.Adopt afterwards enumerative technique to attempt each possible power-division ratios, u of every selection just calculates next step SOC_Init, then next step is also calculated all possible power-division ratios as stated above, until P step estimation range finishes.Then calculate P step estimation range and apply pollutant emission and the oil consumption that obtains after above-mentioned power-division ratios sequence, and choose the power-division ratios sequence that can make above-mentioned objective function reach minimum.
In the present embodiment, the random perturbation of probabilistic model is partly to be the constraint condition service.Originally battery state of charge SOC there is individual hard constraint: SOC＞SOC_Low.Change now probability constraints: P{SOC＞SOC_Low}＞α into, wherein SOC_Low is the lower limit of battery charge state, and the size of α depends on conservative degree.Because there is lower limit in the charge capacity of storage battery, find the solution optimal power allocation than the time also need to consider the impact of model uncertainty to prevent that the electric energy of storage battery from discharging.Uncertainty in each displacement place speed of a motor vehicle has determined the chance that charge capacity crosses the border to a certain extent.The control decision of finally trying to achieve make charge capacity lower than the probability of lower limit greater than α.The chance of so just charge capacity being crossed the border is controlled in the acceptable scope of user.This probability constraints condition can be converted into P ( v i + 1 ≥ 2 I ( s i + 1 - s i ) Q ( SOC _ Init - SOC _ Low ) - v i ) ≥ α
Wherein, the speed of a motor vehicle v in current step iFixing, next step speed of a motor vehicle v i+1The unknown, but satisfy the regularity of distribution
Figure BDA0000094335450000076
I is the battery discharging electric current in this step, and Q is the total capacitance of storage battery, s iReference position s for this step i+1Be the final position in this step, SOC_Init is the initial state-of-charge in current step.
So just obtained the required satisfied inequality condition of discharge current I.Again according to relational expression
Figure BDA0000094335450000081
Obtain the required satisfied inequality condition of motor current power, wherein U 0Be storage battery open-loop voltage, R iBe internal resistance, P emBe power of motor.Get final product to get the inequality constrain of current power-division ratios by the constraint condition of motor current power and total power demand.
Actual vehicle running condition is affirmed and there is gap in model, and the different resulting optimal control rate that storage battery is deposited electric weight is also different, therefore applies to optimize controlled effect u *Afterwards, needs are measured the state-of-charge SOC of storage battery when the real-world operation of vehicle in front, calculate according to SOC and forecast model after upgrading the optimal control that next step should apply.As shown in Figure 4, in current sub-highway section, in the P time domain of current displacement point (k step) beginning, at first obtain vehicle velocity V (k) according to model,, V (k+P), simultaneously, obtain uncertain σ (k) according to model ..., σ (k+P).Then measure the current state-of-charge SOC (k) of battery, calculate controlling quantity u* (k), ..., u* (k+P), apply power-division ratios u* (k) to object, therefore all the time according to the output state of Optimal Ratio control engine and motor, so the energy distributes rationally, has that fuel economy is high, exhaust emissions is few, robustness is good, the technique effect of energy-conserving and environment-protective.
The above is only the preferred embodiment of the present invention, and protection scope of the present invention is not limited in above-mentioned embodiment, and every technical scheme that belongs to the principle of the invention all belongs to protection scope of the present invention.For a person skilled in the art, some improvements and modifications of carrying out under the prerequisite that does not break away from principle of the present invention, these improvements and modifications also should be considered as protection scope of the present invention.

Claims (6)

1. hybrid-power bus energy management method based on the random walk condition model is characterized in that implementation step is as follows:
1) carry out according to the historical speed of a motor vehicle of bus running the historical speed of a motor vehicle-displacement relation that integration obtains bus; Carry out diff according to the historical speed of a motor vehicle of bus running and obtain acceleration/accel-displacement relation; According to the speed of a motor vehicle-displacement relation and the acceleration/accel-displacement relation of each group history, obtain historical average ground speed and the average acceleration of each displacement point on running route, obtain bus at the speed of a motor vehicle random factor of each displacement point according to the variance of the historical speed of a motor vehicle;
2) obtain the power demand in certain predictive displacement section after current displacement point according to historical average ground speed and average acceleration, obtain bus historical motor power variation range in certain predictive displacement section after current displacement point according to speed of a motor vehicle random factor simultaneously, obtain the power-division ratios scope of current displacement point according to certain predictive displacement section internal power demand and historical motor power variation range after current displacement point;
Described step 2) obtaining bus power of motor variation range in certain predictive displacement section after current displacement point according to speed of a motor vehicle random factor in specifically refers to:
A) obtain the speed of a motor vehicle regularity of distribution of every bit in predictive displacement point according to speed of a motor vehicle random factor Be s i+1The historical average ground speed of displacement point;
B) speed of a motor vehicle regularity of distribution satisfies constraint condition
Figure FDA00003463856900012
Obtain the variation range that current of electric I allows, wherein s iBe i displacement point, s i+1Be i+1 displacement point, Q is the total capacitance of storage battery, and SOC_Init is the initial state-of-charge that storage battery is positioned at current displacement point, and SOC_Low is the lower limit of storage battery charge state, and α is the conservative parameter of the battery discharging of setting;
C) basis Obtain power of motor P emThe historical variations scope, U wherein 0Be storage battery open-loop voltage, R iBe internal resistance;
3) with power-division ratios scope combined objective function
Figure FDA00003463856900014
Enumerate the Optimal Ratio that obtains hybrid power, and according to the output state of Optimal Ratio control engine and motor, wherein J fBe the fuel consumption rate of bus engine, J gBe the pollutant emission rate of bus engine, w fFor setting fuel oil consumption weights, w gFor setting the pollutant emission weights, s is the displacement of current displacement point, and E is the operational symbol of averaging, and P is the later predictive displacement point quantity of current displacement point, and u is the power-division ratios sampling value in the power-division ratios scope.
2. the hybrid-power bus energy management method based on the random walk condition model according to claim 1, it is characterized in that: in advance the running route of bus is divided into a plurality of sub-highway sections according to website in described step 1), in described step 3), the displacement of current displacement point refers to the displacement of current displacement point relatively current sub-highway section start position.
3. the hybrid-power bus energy management method based on the random walk condition model according to claim 2, it is characterized in that, carrying out according to the historical speed of a motor vehicle record of bus running the concrete steps that integration obtains the historical speed of a motor vehicle-displacement relation of bus in described step 1) comprises: excursion that will every individual sub-highway section is divided into the N segment according to the time, then to every a bit of basis
∫ t i t i + 1 V ( t ) dt = 1 2 ( t i + 1 - t i ) ( V ( t i ) + V ( t i + 1 ) ) + R
Carry out integration and obtain every a bit of displacement, wherein t iBe the zero hour of i segment, t i+1Be the zero hour of i+1 segment, V (t i) be t iThe speed of a motor vehicle constantly, R is truncated error; Then every a bit of displacement summation is obtained the excursion of bus in current sub-highway section, obtain the historical speed of a motor vehicle-displacement relation of bus according to the historical speed of excursion and current location.
4. the hybrid-power bus energy management method based on the random walk condition model according to claim 1, it is characterized in that, organize the historical speed of a motor vehicle-displacement relation and acceleration/accel-displacement relation according to each in described step 1), obtain that on running route, historical average ground speed and the average acceleration of each displacement point specifically refers to, obtain the crossing in current sub-highway section, if a plurality of crossings are arranged in current highway section choose one of them main crossing according to the comentropy index, the historical speed of a motor vehicle-displacement relation in this zone, crossing of young pathbreaker large according to the historical speed of a motor vehicle is categorized as red light data acquisition and green light data acquisition, then red light data acquisition and green light data acquisition are asked for respectively its historical average ground speed and obtained average acceleration.
5. the hybrid-power bus energy management method based on the random walk condition model according to claim 1, it is characterized in that, organize the historical speed of a motor vehicle-displacement relation and acceleration/accel-displacement relation according to each in described step 1), obtain that on running route, historical average ground speed and the average acceleration of each displacement point refers to: will choose fixing motion vector according to setting step-length, then search two nearest sampling points that are used for obtaining the historical speed of a motor vehicle of the current displacement point of distance, then utilize interpolation arithmetic to obtain the speed of a motor vehicle and the acceleration/accel of current displacement point, and calculate and respectively organize historical data in historical average ground speed and the average acceleration of this displacement point.
6. the hybrid-power bus energy management method based on the random walk condition model according to claim 1, it is characterized in that, in described step 3), power-division ratios scope combined objective function being enumerated the Optimal Ratio that obtains hybrid power specifically refers to: the power-division ratios scope is carried out Interval Discrete, with the end points of Interval Discrete and the Along ent value power-division ratios as sampling, the described objective function of each power-division ratios difference substitution with sampling obtains the power division that meets objective function and is compared to Optimal Ratio.
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