CN102717797A - Energy management method and system of hybrid vehicle - Google Patents

Abstract

The invention discloses an energy management method and system of a hybrid vehicle. The energy management system comprises a server and a whole hybrid vehicle controller, wherein the whole hybrid vehicle controller acquires actual control parameters of the vehicle on a target line through a CAN (Controller Area Network) bus, and sends the acquired actual control parameters to the server by virtue of a GPRS (General Packet Radio Service) module through a network; the server establishes a driver demand power transition probability matrix; an energy management state transition equation is established on the basis of a stochastic dynamic programming algorithm; and the server completes parameter calibration of the whole hybrid vehicle controller, the whole hybrid vehicle controller sends a control parameter, namely demanded motor torque, to the bus according the current state of the vehicle, and a motor controller receives information through the CAN bus and outputs the motor torque, wherein the value of the torque determines the working mode and the fuel economy of the hybrid vehicle.

Description

A kind of hybrid vehicle energy management method and EMS

Technical field

The present invention relates to a kind of hybrid vehicle energy management method and EMS, particularly relate to a kind of hybrid vehicle energy management method and EMS that except that having car load energy distribution function, also has long-range floor data collection and analysis and parameter calibration function.

Background technology

At present, a common problem that exists in the motor vehicle driven by mixed power evolution both at home and abroad is, oil-saving effect is not clearly in the actual track operational process, and this has deviated from the original intention of research hybrid power.The theoretical operating mode that wherein energy management strategy Development process is adopted and the inconsistency of motor vehicle driven by mixed power actual operating mode are that various energy management strategies can not reach a theoretical optimum major reason.Present in addition known hybrid power energy management strategy adopts static logic thresholding control policy; This strategy mainly relies on engineering experience that the logic threshold parameter is set; And these static logic thresholding parameters can not adapt to the dynamic change of vehicle actual condition; Can't guarantee that VE Vehicle Economy is optimum, thereby can't make Full Vehicle System reach maximal efficiency.All the time; The energy management strategy all is that the gordian technique of hybrid power is the emphasis of studying both at home and abroad, and the stochastic dynamic programming energy management strategy of known excellent performance is because the operating mode that adopts in the development process and the inconsistency of actual condition can not get practical application always.

Summary of the invention

The object of the invention is just in order to overcome the deficiency that hybrid vehicle energy management strategy in the prior art can't adapt to the dynamic change of vehicle actual condition; Thereby a kind of hybrid vehicle energy management method is provided; This method is regarded the chaufeur power demand as a Markov process; Through motor vehicle driven by mixed power entire car controller (HCU) actual condition of said vehicle on target line carried out the vehicle speed data collection, pass through the vehicle dynamics formula according to the vehicle speed data of being gathered then, try to achieve each instantaneous power demand; Obtain the transition probability matrix of chaufeur demand power, set up the markov probabilistic model of chaufeur demand power; Set up the energy management problem based on the stochastic dynamic programming algorithm then; Being specially and turning to finite space with chaufeur power demand, motor output torque, battery SOC and the speed of a motor vehicle are discrete, is state variable with SOC value of battery, the speed of a motor vehicle, gear, chaufeur demand power, constitutes state space X; With motor output torque as decision variable G; With fuel oil consumption, engine emission, SOC value of battery is cost function J, with the maximum of the speed of a motor vehicle, battery SOC, motor output torque and minimum value as constraint, i.e. the boundary condition of solution procedure; Set up the state transition equation of chaufeur demand power; And using modified policy iteration method carries out iterative, and the best decision variable G in each step combines and constitutes the energy management strategy that is fit to this circuit, and concrete form is: (T _m(k))=π (SOC (k), ω _w(k), g (k), T _Dem(k)), T in the formula _m(k) motor torque of expression demand, SOC (k) representes battery charge state, ω _w(k) the expression speed of a motor vehicle, g (k) representes automobile gear level, T _Dem(k) expression chaufeur demand torque, this energy management strategy is the motor booster type, makes driving engine be operated in efficient district as far as possible through the output of regulating motor torque; Method through long-range demarcation is to the controlled variable of HCU, promptly according to current vehicle state (SOC (k), ω again _w(k), g (k), T _Dem(k)) motor output torque of confirming upgrades with the mode of function match or data sheet, and HCU is dealt into the value of this torque the control of accomplishing on the CAN bus motor.

In the said hybrid vehicle energy management method, said motor vehicle driven by mixed power entire car controller (HCU) is gathered vehicle speed data through the CAN bus, and through the GPRS module vehicle speed data of being gathered is sent to server through network.

In the said hybrid vehicle energy management method, the ICP/IP protocol module that said server by utilizing LABVIEW software inhouse is integrated receives said vehicle speed data, and accomplishes demonstration and store operational.

In the said hybrid vehicle energy management method, the speed of a motor vehicle time history of the said LABVIEW software storage of said server by utilizing MATLAB software transfer through statistical analysis, obtains the actual condition data of said vehicle on said target line.

In the said hybrid vehicle energy management method, the strategy that the said LABVIEW of said server by utilizing will generate is updated in the said motor vehicle driven by mixed power entire car controller (HCU) with the good function representation of form or match and through network.

The present invention also provides a kind of hybrid vehicle energy management system; This system comprises server and motor vehicle driven by mixed power entire car controller (HCU); Said motor vehicle driven by mixed power entire car controller (HCU) is gathered the speed information of said vehicle on target line through the CAN bus, and through the GPRS module the said working control parameter of being gathered is sent to said server through network; The integrated ICP/IP protocol module of said server by utilizing LABVIEW software inhouse receives the said working control parameter of storage; The said LABVIEW software of said server by utilizing MATLAB software transfer receives the said working control parameter of storage, sets up chaufeur demand power transition probability matrix through the vehicle dynamics formula; Set up the energy management state transition equation based on the stochastic dynamic programming algorithm then, the SDP tool box of using in the said MATLAB software carries out iterative; The strategy that the said LABVIEW of said server by utilizing generates iterative is updated in the said motor vehicle driven by mixed power entire car controller (HCU) with the good function representation of form or match and through network remote; Accomplish the parameter calibration of said motor vehicle driven by mixed power entire car controller (HCU); Motor vehicle driven by mixed power entire car controller (HCU) sends controlled variable according to the vehicle current state on bus, i.e. the motor torque of demand.

The invention has the advantages that:

1, through the method for long-range demarcation the controlled variable of HCU is upgraded, HCU accomplishes the realization of strategy.This fuel economy that raising China is had the hybrid power bus of fixed line has very large practical significance with its discharging of reduction.

2, realized " line one strategy ", can improve the fuel economy of hybrid power bus long-time running in fact, and when the design energy problem of management, can take all factors into consideration its emission behavior.

Description of drawings

Fig. 1 is a hybrid vehicle energy management system schematic of the present invention;

Fig. 2 is the structural representation of the motor vehicle driven by mixed power entire car controller HCU in the hybrid vehicle energy management of the present invention system.

The specific embodiment

Below in conjunction with the accompanying drawing and the specific embodiment the present invention is further specified.

At first introduce the system principle of Markov process:

The basic conception of Markov process is " transfer " of system's " state " and state.When system was described by the variable-value of definition status fully, the system of we can say was in a state.If the description variable of system changes to the particular value of another state from the particular value of a state, at this moment, we just say that system realizes state transitions.

Vehicle driver's behavior is a very representative type Markov process, and the pairing power demand of the driving behavior of chaufeur is exactly a state, to another driving behavior, is state transitions from a driving behavior.

Chaufeur power demand P _{Dr_dem}Span can disperse and be the set of limited value, that is:

$P_{\mathrm{dr}\_\mathrm{dem}}\∈\{P_{\mathrm{dr}\_\mathrm{dem}}^1,P_{\mathrm{dr}\_\mathrm{dem}}^2,...,P_{\mathrm{dr}\_\mathrm{dem}}^{N_s}\}---\left(1\right)$

Similar with the chaufeur power demand, speed V _VelThe set of limited value of span discretization, that is:

$V_{\mathrm{vel}}\∈\{V_{\mathrm{vel}}^1,V_{\mathrm{vel}}^2,...,V_{\mathrm{vel}}^{N_w}\}---\left(2\right)$

Chaufeur power demand transition probability p _{Ij, k}, that is:

$\mathrm{Pr}\left\{P_{\mathrm{dr}\_\mathrm{dem}}^m\right|P_{\mathrm{dr}\_\mathrm{dem}}^i,V_{\mathrm{vel}}^j\}=p_{\mathrm{ij},k},\underset{k=1}{\overset{N_s}{\mathrm{\Σ}}}{p}_{\mathrm{ij},k}=1,$ i,m＝1,2,...,N _s,j＝1,2,...,N _w (3)

In the formula, N _s, N _wBe respectively chaufeur power demand and speed of a motor vehicle discretization number,

-time t _kThe time power demand and the speed of a motor vehicle,

-time t _K+1The time power demand.

The implication of above-mentioned formula is: at moment k, the chaufeur demand power does

The speed of a motor vehicle does

Condition under, the chaufeur demand power is at t _K+1Constantly transfer to

Probability.

According to vehicle time-speed of a motor vehicle floor data, utilization vehicle dynamics formula:

$P_{\mathrm{dr}\_\mathrm{dem}}=\frac{V_{\mathrm{vel}}}{360{0\mathrm{\η}}_T}(\mathrm{Gf}\cos \mathrm{\α}+G\sin \mathrm{\α}+\frac{C_D{\mathrm{AV}}_{\mathrm{vel}}^2}{21.15}+\mathrm{\δ}\frac{G}{g}\frac{{\mathrm{dV}}_{\mathrm{vel}}}{\mathrm{dt}})---\left(4\right)$

In the formula, P _{Dr_dem}-vehicle ' power, V _Vel-the speed of a motor vehicle, f-coefficient of rolling resistance, A-wind area, C _D-aerodynamic drag factor, α-road grade angle, G-vehicle gravity, g-acceleration due to gravity, δ-automobile correction coefficient of rotating mass,

-running car acceleration/accel, η _TMechanical efficiency of power transmission) calculates current time t _kPower demand is P _{Dr_rdem}, the speed of a motor vehicle is V _VelUnder the condition, next is t constantly _K+1Power demand, the chaufeur power demand one the step transition probability can be expressed as through maximal possibility estimation

${\hat{p}}_{\mathrm{ij},k}\stackrel{\mathrm{\Δ}}{=}\frac{n_{\mathrm{ij},m}}{n_{\mathrm{ij}}}---\left(5\right)$

N in the formula _{Ij, m}Expression chaufeur power demand from

Transfer to

Number of times,

Expression

Shift total degree, all transition probabilities are formed transition probability matrix P.

Consider a stochastic dynamic programming M=(X, G, P, L) problem has finite state space X, limited action space G, cost function L:X * G → L and transitionmatrix P (this is above-mentioned transition probability matrix P).At each constantly, system is in the some state X in the finite state space.The finite aggregate G that the behavior that a system can take is all arranged for each the state x ∈ X in the state space.System evolves according to state transition probability matrix P, and P (x, G, x ') expression system transfers to the probability of state x ' after having taked behavior G under the state x.Cost function is by L (x, G, x ') expression, and promptly system takes behavior G to transfer to the cost that state x ' is paid from state x.Strategy π is the sequence that state is mapped to behavior, and it has pointed out to shift constantly at each, system for the present located state the behavior that should take.Value function J has defined the accumulated value of the cost function in the future that each state x expects under certain tactful π.And optimum value function J is defined as accumulated value average of cost function in future of the minimum of each state.Write out recurrence relation according to the Bellman principle of optimality:

$J_{\mathrm{\π}}^{s+1}\left(x\right)=\underset{G}{\min }\underset{x^{\′}}{\mathrm{\Σ}}{p}_{\mathrm{ij},k}(L(x.G,x^{\′})+J_{\mathrm{\π}}^s\left(x^{\′}\right))---\left(6\right)$

In the formula, s-iterations, the state that x '-system is new.

The definition of optimal value function has been arranged, and optimum behavior is selected according to minimum expectation value principle by system, i.e. selection makes the minimum behavior of the expectation value function of each state as optimum behavior

${\mathrm{\π}}^{*}\left(x\right)=\underset{\mathrm{\μ}\∈G}{\arg }\min \underset{x^{\′}}{\mathrm{\Σ}}{p}_{\mathrm{ij},k}(L(x,G,x^{\′})+J_{\mathrm{\π}}^s\left(x^{\′}\right))---\left(7\right)$

For all states, J in the formula _πThe cost function that expression stragetic innovation process obtains need remove to upgrade cost function, up to J after a new strategy obtains _πConverging to this iterative process of predetermined value finishes.

Specific to hybrid vehicle energy management problem of the present invention; Be about to the discrete finite space that turns to of chaufeur power demand, motor output torque, battery SOC and the speed of a motor vehicle; With SOC value of battery, the speed of a motor vehicle, gear, chaufeur demand power is state variable, constitutes state space X, with motor output torque as decision variable G; Be weighted to cost function J with fuel oil consumption, engine emission, SOC value of battery; As constraint, i.e. the boundary condition of solution procedure is set up the state transition equation (6) of chaufeur demand power with the maximum of the speed of a motor vehicle, battery SOC, motor output torque and minimum value; And using modified policy iteration method (the SDP tool box among the MATLAB) carries out iterative, the best decision variable G in each minimum step of all cost function J combined constitute the energy management strategy π that is fit to this circuit ^*, concrete form is: (T _m(k))=π (SOC (k), ω _w(k), g (k), T _Dem(k)) (T in the formula _m(k) motor torque of expression demand, SOC (k) representes battery charge state, ω _w(k) the expression speed of a motor vehicle, T _Dem(k) expression chaufeur demand torque), this energy management strategy is the motor booster type, makes driving engine be operated in efficient district as far as possible through the output of regulating motor torque; Method through long-range demarcation is to the controlled variable of HCU again, and promptly HCU is according to current vehicle state (SOC (k), ω _w(k), g (k), T _Dem(k)) motor output torque of confirming upgrades with the mode of function match or data sheet, and HCU is dealt into the value of this torque the control of accomplishing on the CAN bus motor.Concrete principle and implementation procedure according to hybrid vehicle energy management of the present invention system are:

At first, regard the chaufeur power demand as a Markov process, hybrid-power bus is scheduled to last the vehicle speed data collection about about one to two week at the road condition on the target line, obtain the actual condition of this circuit;

Secondly; Try to achieve each instantaneous chaufeur power demand based on this floor data through above-mentioned vehicle dynamics formula (4), and then obtain the transition probability matrix of chaufeur power demand Markov process according to above-mentioned formula (1) (2) (3) (4) (5);

Once more, try to achieve the energy management strategy that is fit to this circuit with the stochastic dynamic programming method.

At last, through the method for long-range demarcation the controlled variable of HCU is upgraded, HCU accomplishes the realization of strategy.

This fuel economy that raising China is had the hybrid power bus of fixed line has very large practical significance with its discharging of reduction.

System architecture

This system comprises hybrid power entire car controller (HCU) and server software two parts, like Fig. 1.

(1) hardware configuration

HCU structure such as Fig. 2; 32 PowerPC series monolithic MPC5644A that main control chip MCU adopts Freescale company to develop to power drive system specially; Be connected on the CAN bus through the CAN interface circuit; The information that MCU mainly obtains from bus has SOC value of battery, driving engine current torque, motor current torque, current gear, current vehicle speed, and the information that sends on the CAN bus has motor torque, motor torque and accelerator open degree.Main control chip links to each other with the GPRS module through serial communication interface circuit; MCU is the energy distribution controlled variable from far-end server through the information of the long-range reception of GPRS, and the information that sends to far-end server through GPRS is the speed of a motor vehicle-time history of hybrid power bus on certain bar public bus network.The acceleration pedal signal of chaufeur is issued MCU through modulate circuit, and power circuit, crystal oscillating circuit, reset circuit are formed the reliability service of the minimum system circuit assurance hardware of controller.

(2) server software structure

Server software is based on LABVIEW and the MATLAB Mixed-Programming Technology is carried out design-calculated; LABVIEW is the foreground display layer; Radical function is a telecommunication of being responsible for realization and HCU; Accomplish the transmission of floor data and controlled variable; Possess data storage and Presentation Function, can be through the beginning and the end of gathering with HCU telecommunication control data, and can control, check the operation of model among the MATLAB/SIMULINK through interfacing (ActiveX, DDE, Mathscript) or interface facility bag SIT.MATLAB is an operation layer; Receive the vehicle speed data that LABVIEW gathers, obtain the speed of a motor vehicle time history of the hybrid power bus of this circuit after treatment, calculate transition probability matrix with statistical method; Set up and find the solution the energy management problem based on the stochastic dynamic programming method then

Workflow

1) at first the hybrid power bus in the operation in week real-world operation circuit enterprising behavior phase one to two; The controlled variable of energy management is one group of static threshold parameter based on engineering experience among the HCU at this moment; HCU can be through sampling frequency online acquisition bus the speed of a motor vehicle on real-world operation route of CAN bus with 1Hz, and serial ports bonded assembly GPRS module sends to server with these data through network.

2) the integrated ICP/IP protocol module of server end LABVIEW software inhouse is utilized the vehicle speed data on the software collection network interface card of writing out, accomplishes to show and store operational.

3) MATLAB calls the speed of a motor vehicle time history of LABVIEW storage; Bad point data is rejected; The bad point here is meant because a variety of causes (like vehicle trouble etc.) cause obviously do not possess representational data; Rejecting is not these data is listed in the statistics of back, obtains many actual operating mode data of bus on this circuit.

4) to a large amount of vehicle speed datas of obtaining, through the vehicle dynamics formula, counter asking obtains per moment chaufeur demand power, obtains transition probability matrix according to the flow processing of formula (1) (2) (3) (4) (5) in the above-mentioned principle.

5) set up the energy management problem based on the stochastic dynamic programming algorithm then; Being specially and turning to finite space with chaufeur power demand, motor output torque, battery SOC and the speed of a motor vehicle are discrete, is state variable with SOC value of battery, the speed of a motor vehicle, gear, chaufeur demand power, constitutes state space X; With motor output torque as decision variable G; With fuel oil consumption, engine emission, SOC value of battery be weighted to cost function J, with the maximum of the speed of a motor vehicle, battery SOC, motor output torque and minimum value as constraint, i.e. the boundary condition of solution procedure; Write out state transition equation (6), the SDP tool box in the Application of MATLAB carries out iterative.

The strategy that 6) will generate through LABVIEW at last is updated among the HCU with the good function representation of form or match and through network, and HCU finally realizes this energy management strategy.

Claims (8)

1. hybrid vehicle energy management method may further comprise the steps:

(1) this method is regarded the chaufeur power demand as a Markov process, through motor vehicle driven by mixed power entire car controller (HCU) actual condition of said vehicle on target line is carried out the vehicle speed data collection;

(2) according to the vehicle speed data of being gathered, try to achieve each instantaneous chaufeur power power demand through the vehicle dynamics formula, obtain the transition probability matrix of chaufeur demand power, set up the markov probabilistic model of chaufeur demand power;

(3) set up the energy management problem of this motor vehicle driven by mixed power based on the stochastic dynamic programming algorithm, set up the state transition equation of chaufeur demand power;

(4) using modified policy iteration method carries out iterative to the state transition equation of said chaufeur demand power, and the decision variable G in each step that solves, these decision variables combine and constitute the energy management strategy that is fit to this circuit;

(5) through long-range demarcation the controlled variable of HCU, i.e. vehicular electric machine output torque T _m, be updated among the HCU with the mode of function match or data sheet.

2. hybrid vehicle energy management method according to claim 1; Wherein said motor vehicle driven by mixed power entire car controller (HCU) is gathered vehicle speed data through the CAN bus, and through the GPRS module vehicle speed data of being gathered is sent to server through network.

3. hybrid vehicle energy management method according to claim 1, the ICP/IP protocol module that wherein said server by utilizing LABVIEW software inhouse is integrated receives said vehicle speed data, and accomplishes demonstration and store operational.

4. hybrid vehicle energy management method according to claim 1; The vehicle speed data of the said LABVIEW software storage of wherein said server by utilizing MATLAB software transfer; Through statistical analysis, obtain the actual condition data of said vehicle on said target line.

5. hybrid vehicle energy management method according to claim 1, the strategy that the said LABVIEW of wherein said server by utilizing will generate is updated in the said motor vehicle driven by mixed power entire car controller (HCU) with the good function representation of form or match and through network.

6. hybrid vehicle energy management method according to claim 1, the vehicle dynamics formula that is wherein adopted is:

$P_{\mathrm{dr}\_\mathrm{dem}}=\frac{V_{\mathrm{vel}}}{3600{\mathrm{\η}}_T}(\mathrm{Gf}\cos \mathrm{\α}+G\sin \mathrm{\α}+\frac{C_D{\mathrm{AV}}_{\mathrm{vel}}^2}{21.15}+\mathrm{\δ}\frac{G}{g}\frac{{\mathrm{dV}}_{\mathrm{vel}}}{\mathrm{dt}});$

Wherein, P _{Dr_dem}Be vehicle ' power, V _VelBe the speed of a motor vehicle, f is a coefficient of rolling resistance, and A is a wind area, C _DBe aerodynamic drag factor, α is the road grade angle, and G is a vehicle gravity, and g is an acceleration due to gravity, and δ is the automobile correction coefficient of rotating mass,

Be running car acceleration/accel, η _TBe the vehicle transmission system mechanical efficiency.

7. hybrid vehicle energy management method according to claim 1, wherein said energy management problem is specially: with the discrete finite space that turns to of chaufeur power demand, motor output torque, battery SOC and the speed of a motor vehicle; With SOC value of battery, the speed of a motor vehicle, gear, chaufeur demand power is state variable, constitutes state space X; With motor output torque T _mAs decision variable G; With fuel oil consumption, engine emission, SOC value of battery is cost function J; With the maximum of the speed of a motor vehicle, battery SOC, motor output torque and minimum value as constraint, i.e. the boundary condition of solution procedure; Thereby set up the state transition equation of chaufeur demand power.

8. hybrid vehicle energy management system; This system comprises server and motor vehicle driven by mixed power entire car controller (HCU); Said motor vehicle driven by mixed power entire car controller (HCU) is gathered the speed information of said vehicle on target line through the CAN bus, and through the GPRS module the said speed information of being gathered is sent to said server through network; The integrated ICP/IP protocol module of said server by utilizing LABVIEW software inhouse receives the said speed information of storage; The said LABVIEW software of said server by utilizing MATLAB software transfer receives the said speed information of storage, through the Converse solved transition probability matrix of setting up the chaufeur demand power of vehicle dynamics formula; Set up the energy management state transition equation based on the stochastic dynamic programming algorithm then; The SDP tool box of using in the said MATLAB software carries out iterative; Obtain the controlled variable of said motor vehicle driven by mixed power entire car controller (HCU), i.e. the vehicular electric machine output torque; The controlled variable that the said LABVIEW of said server by utilizing generates iterative is with form or the good function representation of match; And be updated in the said motor vehicle driven by mixed power entire car controller (HCU) through network remote; Accomplish the controlled variable of said motor vehicle driven by mixed power entire car controller (HCU) and demarcate, said motor vehicle driven by mixed power entire car controller (HCU) thus be dealt into the value of said vehicular electric machine output torque the control of accomplishing on the CAN bus motor.

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