CN104477045A - Hybrid electric vehicle compound power supply with maximally optimized energy efficiency and method of hybrid electric vehicle compound power supply - Google Patents

Abstract

The invention discloses a hybrid electric vehicle compound power supply with maximally optimized energy efficiency and a method of the hybrid electric vehicle compound power supply. The compound power supply comprises a storage battery, a super-capacitor and a DC/DC converter, wherein the super-capacitor is serially connected with the DC/DC converter and then parallelly connected with the storage battery. The optimization method includes the steps: building mathematic models of the storage battery, the super-capacitor and the DC/DC converter; solving the loss of each model and the total power loss; concluding limiting conditions of the total loss to obtain an energy efficiency maximizing optimization model; solving by an approximate programming method; approximating a target function and constraint conditions of the optimization model as a linear function, solving the linear function by a simplex method, and taking an optimal solution meeting original conditions as a final solution of the optimization model. Power loss of an optimized compound power supply energy storage system is greatly reduced as compared with power loss before optimization, and energy use rate is increased. Working points of high-efficiency areas of the storage battery and the super-capacitor are increased and more densely distributed.

Description

Energy efficiency maximizes the hybrid vehicle composite power source under optimizing and method thereof

Technical field

The present invention relates to a kind of closed-center system and energy efficiency optimization method thereof of hybrid vehicle, ultracapacitor forms composite power source through DC/DC changer is in parallel with storage battery, and is optimized composite power source energy efficiency.

Background technology

Due to rising steadily of oil price and going from bad to worse of global warming problem, auto trade always exploration one by the solution improving fuel utilization ratio and reduce for the purpose of CO2 emissions, hybrid vehicle relies on the advantage of its energy-saving and environmental protection to develop into a kind of inexorable trend.

But, the tractive performance of current hybrid vehicle is still less than conventional fuel oil automobile, its major cause is that its specific power of energy-storage system of accumulator is lower, cycle life is short, hybrid vehicle at instantaneous starting with when accelerating battery be difficult to meet load high power density demand and at snap catch time energy fully reclaim, thus strongly limit the fast development of hybrid vehicle.For this problem, ultracapacitor relies on the fast and advantage such as to have extended cycle life of its high power density, charge/discharge rates to provide actv. solution.Combined with ultracapacitor by storage battery and form composite power source and carry out power back-off to storage battery, this bring very large performance to improve can to undoubtedly hybrid vehicle closed-centre system.

Summary of the invention

For the problems referred to above that hybrid vehicle composite power source in prior art exists, the invention provides a kind of energy efficiency and maximize the hybrid vehicle composite power source under optimizing and method thereof.Hybrid vehicle composite power source is made up of storage battery, ultracapacitor and DC/DC changer, and ultracapacitor regulates its voltage to mate work with battery by DC/DC changer automatically, effectively protects storage battery.Namely the energy efficiency improving hybrid power system reduces the watt loss of this system.Establish the math modeling of storage battery in composite power source closed-centre system, ultracapacitor and DC/DC changer respectively, solve the watt loss of modules, thus obtain the total power loss of hybrid power system.Induction and conclusion goes out the limiting condition of overall loss, just can obtain the maximized Optimized model of hybrid power system energy efficiency, because this Optimized model belongs to nonlinear programming category, therefore adopts approximating programming method to solve.

The technical solution adopted for the present invention to solve the technical problems is:

Energy efficiency maximizes the hybrid vehicle composite power source under optimizing, comprise storage battery, ultracapacitor and DC/DC changer, ultracapacitor is in parallel with storage battery again after connecting with DC/DC changer, storage battery as main power source, ultracapacitor and bidirectional DC-DC converter accessory feed in series.

Energy efficiency maximizes the model optimization method of the hybrid vehicle composite power source under optimizing, and specifically comprises the steps:

1) math modeling of storage battery, ultracapacitor and DC/DC changer is set up;

2) solve step 1) in the loss of each model, thus obtain the total power loss of hybrid power system;

3) induction and conclusion goes out the limiting condition of overall loss, obtains the maximized Optimized model of hybrid power system energy efficiency; Because this Optimized model belongs to nonlinear programming category, approximating programming method is adopted to solve;

4) objective function in Optimized model and constraint condition are approximately linear function, and the span of variable is limited, obtain an Approximate linear programming problem, then solve it by simplex method, it is met the last solution of optimal solution as Optimized model of initial condition.

Further, described battery model is a dynamic system integrating four kinds of parameters, and these four kinds of parameters comprise storage battery charge state SOC _b, surface temperature T _band relevant to internal capacitor two kinds of voltages ultracapacitor model is by internal capacitor C _uc, shunt resistance and series resistance composition; DC/DC changer is two-way DC/DC changer, and structure is non-isolated half-bridge structure; Described Optimized model for objective function be:

min(Φ _hess)＝min(Φ _b+Φ _uc+Φ _dcdc)

Wherein, Φ _hessfor hybrid vehicle composite power source closed-centre system overall loss; for the internal loss of storage battery; for the internal loss of ultracapacitor; Φ _dcdcfor the internal loss of DC/DC changer.

Further, described storage battery is battery pack, by individual identical battery cell composition, for series connection number; for number of parallel;

Battery model is:

${\stackrel{\·}{\mathrm{SOC}}}_b=\frac{-I_b^{\mathrm{cell}}}{Q_b}$

${\stackrel{\·}{U}}_b^{\left(1\right)}=\frac{I_b^{\mathrm{cell}}}{C_b^{\left(1\right)}}-\frac{U_b^{\left(1\right)}}{R_b^{\left(1\right)}{C}_b^{\left(1\right)}}$

${\stackrel{\·}{U}}_b^{\left(2\right)}=\frac{I_b^{\mathrm{cell}}}{C_b^{\left(2\right)}}-\frac{U_b^{\left(2\right)}}{R_b^{\left(2\right)}{C}_b^{\left(2\right)}}$

${\stackrel{\·}{T}}_b=({\mathrm{\Φ}}_b^{\mathrm{cell}}-h{\mathrm{\Σ}}_b(T_b-T_{\mathrm{cool}}))/\left(m_b{c}_b\right)$

Wherein, for the electric current of cell; Cell resistance and electric capacity depend on SOC and the temperature of battery; Q _bfor battery rated storage capacity; m _bfor battery quality; c _bfor specific heat capacity; ∑ _bfor the exchange surface with cooling system; T _coolfor chilling temperature; H is coefficient of thermal conductivity; for inside battery loss;

The internal loss of storage battery for:

${\mathrm{\Φ}}_b^{\mathrm{cell}}=R_b^{\left(0\right)}{\left(I_b^{\mathrm{cell}}\right)}^2+\frac{{\left(U_b^{\left(1\right)}\right)}^2}{R_b^{\left(1\right)}}+\frac{{\left(U_b^{\left(2\right)}\right)}^2}{R_b^{\left(2\right)}}+{\mathrm{\α}}_b{I}_b^{\mathrm{cell}}$

Wherein, for the internal resistance of battery; α _bfor inside battery dissipation factor.

Further, described ultracapacitor by individual electric capacity monomer composition, for series connection number; for number of parallel;

Ultracapacitor model is:

${\stackrel{\·}{U}}_C=-\frac{I_{\mathrm{uc}}^{\mathrm{cell}}}{C_{\mathrm{uc}}}-\frac{U_C}{R_{\mathrm{uc}}^{\mathrm{laek}}{C}_{\mathrm{uc}}}$

${\stackrel{\·}{T}}_{\mathrm{uc}}=({\mathrm{\Φ}}_{\mathrm{uc}}^{\mathrm{cell}}-h{\mathrm{\Σ}}_{\mathrm{uc}}(T_{\mathrm{uc}}-T_{\mathrm{cool}}))/\left(m_u{c}_u\right)$

${\stackrel{\·}{\mathrm{SOC}}}_{\mathrm{uc}}=\frac{-I_{\mathrm{uc}}^{\mathrm{cell}}}{Q_{\mathrm{uc}}}$

Wherein, relevant to the drain current of ultracapacitor inside; for the electric current of monolithic capacitor; Q _ucfor rated capacitor memory capacity; m _ufor cond quality; c _ufor specific heat capacity; ∑ _ucfor the exchange surface with cooling system; T _coolfor chilling temperature; H is coefficient of thermal conductivity; T _ucfor surface temperature; U _cfor ultracapacitor builtin voltage, the electric capacity C of cond _ucdetermine U _csize; SOC _bfor cond state-of-charge; for capacitor internal loss;

The internal loss of ultracapacitor for:

${\mathrm{\Φ}}_{\mathrm{uc}}^{\mathrm{cell}}=\frac{{\left(U_C\right)}^2}{R_{\mathrm{uc}}^{\mathrm{leak}}}+R_{\mathrm{uc}}^{\left(0\right)}{\left(I_{\mathrm{uc}}^{\mathrm{cell}}\right)}^2+{\mathrm{\α}}_{\mathrm{uc}}{I}_{\mathrm{uc}}^{\mathrm{cell}}$

Wherein, for the internal resistance of ultracapacitor; α _ucfor the internal loss factor of ultracapacitor.

Further, described DC/DC changer is two-way DC/DC changer;

DC/DC changer model is:

$L_{\mathrm{dcdc}}\frac{{\mathrm{dI}}_{\mathrm{uc}}}{\mathrm{dt}}=-R_{\mathrm{dcdc}}{I}_{\mathrm{uc}}+U_{\mathrm{uc}}-(1-D)U_b$

I _dcdc＝(1-D)I _uc

Wherein, L _dcdcfor with resistive R _dcdcfilter inductance; I _ucfor condenser current; U _ucfor condenser voltage; U _bfor accumulator battery voltage; D is dutycycle;

The internal loss Φ of DC/DC changer _dcdcfor:

Φ _dcdc＝R _dcdcI _uc ²

Further, described constraint condition is:

${\stackrel{\·}{U}}_C=\frac{-U_C}{R_{\mathrm{uc}}^{\mathrm{leak}}{C}_{\mathrm{uc}}}-\frac{I_{\mathrm{uc}}}{N_{\mathrm{uc}}^{\left(p\right)}{C}_{\mathrm{uc}}}$

(1-β)U _b≤U _uc

β≤β _max＜1

$U_{\mathrm{uc}}\≤N_{\mathrm{uc}}^{\left(s\right)}{U}_{\mathrm{uc}}^{\mathrm{cell}-\max }$

$U_b\≤N_b^{\left(s\right)}{U}_b^{\mathrm{cell}-\max }$

$0\≤\left|I_b\right|\≤I_b^{\max }$

$0\≤\left|I_{\mathrm{uc}}\right|\≤I_{\mathrm{uc}}^{\max }$

Wherein, β is the battery voltage range constraint factor.

The invention has the beneficial effects as follows, the math modeling of the hybrid power system set up reflects relation that is complicated and that be closely connected between each parameter of internal system efficiently and accurately; Hybrid power system watt loss after optimization obviously reduces, and no matter be battery or electric capacity, both efficiency is significantly increased, and after optimizing, the operation point of high efficient area is more concentrated closely; The cycle life that energy efficiency maximizes extending composite power source has great significance, and utilizes resource to the full extent simultaneously, gives full play to the preceence of resource.

Accompanying drawing explanation

Fig. 1 is the system model figure of hybrid vehicle composite power source.

Fig. 2 is battery model figure.

Fig. 3 is ultracapacitor illustraton of model.

Fig. 4 is DC/DC changer illustraton of model.

Detailed description of the invention

Below in conjunction with accompanying drawing, the present invention is described in further detail.

The present invention, by setting up the math modeling of storage battery, ultracapacitor and DC/DC changer in hybrid vehicle composite power source closed-centre system, obtains energy efficiency Optimized model.Objective function due to Optimized model is nonlinear, and constraint condition is also all nonlinear function substantially, so this optimization problem belongs to nonlinear programming category, approximating programming method can be adopted solve, its basic thought is that objective function and constraint condition are approximately linear function, and the span of variable is limited, thus obtain an Approximate linear programming problem, it is solved again by simplex method, it is met the last solution of optimal solution as optimization problem of initial condition, concrete solution procedure is as follows:

(1) given feasible initial point, getting one-dimensional nonlinear optimization problem is example, and feasible initial point is assumed to be step-length limits step-length coefficient of reduction β ∈ (0,1), permissible error ε, makes k=1;

(2) at an x ^kplace, by objective function f (X) and limiting condition g _i(X), h _j(X) get first approximation by Taylor series expansion, obtain Approximate linear programming problem:

$\begin{array}{c}\min f\left(X\right)\≈f\left(X^k\right)+\▿f{\left(X^k\right)}^T(X-X^k)\\ g_i\left(X\right)\≈g_i\left(X^k\right)+\▿g_i{\left(X^k\right)}^T(X-X^k)\≥0\\ i=1,...,m\\ h_j\left(X\right)\≈h_j\left(X^k\right)+\▿h_j{\left(X^k\right)}^T(X-X^k)\≥0,\\ j=1,...,1\end{array}$

(3) on the basis of above-mentioned Approximate linear programming problem, increase the Linear Constraints of one group of restricted step, because usual of linear approximation degree of approximation near breaking up point is higher, so need to be limited the span of variable, the constraint condition increased is:

$|x_j-x_j^k|\≤{\mathrm{\δ}}_j^k,j=1,...,n$

Solve this linear programming problem, obtain optimal solution X ^k+1;

(4) X is checked ^k+1whether point is feasible to former constraint condition.If X ^k+1feasible to former constraint, then go back to step (5); Otherwise, reduce step-length restriction, order return step (3), heavily separate current linear programming problem;

(5) precision is judged: if then put X ^k+1for approximate optimal solution, otherwise, order ${\mathrm{\δ}}_j^{k+1}={\mathrm{\δ}}_j^k$ $(j=1,...,n),k=k+1,$ Return step (2).

In FIG, defining battery pack is individual identical battery cell composition, here for series connection number, and for number of parallel.The voltage and current of battery pack can be expressed as:

$U_b=N_b^{\left(s\right)}{V}_b^{\mathrm{cell}},I_b=N_b^{\left(p\right)}{I}_b^{\mathrm{cell}}---\left(1\right)$

Wherein with be respectively the voltage and current of cell.In like manner, bank of super capacitors by individual electric capacity monomer composition, total voltage and total current are:

$U_{\mathrm{uc}}=N_{\mathrm{uc}}^{\left(s\right)}{V}_{\mathrm{uc}}^{\mathrm{cell}},I_{\mathrm{uc}}=N_{\mathrm{uc}}^{\left(p\right)}{I}_{\mathrm{uc}}^{\mathrm{cell}}---\left(2\right)$

DC bus current I _dc=I _b+ I _uc, the horsepower output of composite power source is P _dc=V _dc× I _dc.

In fig. 2, battery model is a dynamic system integrating four kinds of parameters, and these four kinds of parameters comprise its state-of-charge SOC _b, surface temperature T _band relevant to internal capacitor two kinds of voltages

Complete model is as follows:

${\stackrel{\·}{\mathrm{SOC}}}_b=\frac{-I_b^{\mathrm{cell}}}{Q_b}---\left(3\right)$

${\stackrel{\·}{U}}_b^{\left(1\right)}=\frac{I_b^{\mathrm{cell}}}{C_b^{\left(1\right)}}-\frac{U_b^{\left(1\right)}}{R_b^{\left(1\right)}{C}_b^{\left(1\right)}}---\left(4\right)$

${\stackrel{\·}{U}}_b^{\left(2\right)}=\frac{I_b^{\mathrm{cell}}}{C_b^{\left(2\right)}}-\frac{U_b^{\left(2\right)}}{R_b^{\left(2\right)}{C}_b^{\left(2\right)}}---\left(5\right)$

${\stackrel{\·}{T}}_b=({\mathrm{\Φ}}_b^{\mathrm{cell}}-h{\mathrm{\Σ}}_b(T_b-T_{\mathrm{cool}}))/\left(m_b{c}_b\right)---\left(6\right)$

Wherein, with depend on SOC and the temperature of battery; Q _bfor battery rated storage capacity; m _bfor battery quality; c _bfor specific heat capacity; ∑ _bfor the exchange surface with cooling system, T _coolfor chilling temperature, h is coefficient of thermal conductivity; for inside battery loss.

Finally, cell pressure can be expressed as:

$U_b=E_b-R_b^{\left(0\right)}{I}_b^{\mathrm{cell}}-U_b^{\left(1\right)}-U_b^{\left(2\right)}---\left(7\right)$

E in formula (7) _bfor non-loaded cell pressure, by SOC _band T _bdetermine.Inside battery loss can be expressed as:

${\mathrm{\Φ}}_b^{\mathrm{cell}}=R_b^{\left(0\right)}{\left(I_b^{\mathrm{cell}}\right)}^2+\frac{{\left(U_b^{\left(1\right)}\right)}^2}{R_b^{\left(1\right)}}+\frac{{\left(U_b^{\left(2\right)}\right)}^2}{R_b^{\left(2\right)}}+{\mathrm{\α}}_b{I}_b^{\mathrm{cell}}---\left(8\right)$

α _bfor inside battery dissipation factor, equally by SOC _band T _bdetermine.

In figure 3, ultracapacitor builtin voltage is U _c, cond C _ucdetermine U _ucsize, surface temperature is T _uc, the relation between them is as follows:

${\stackrel{\·}{U}}_C=-\frac{I_{\mathrm{uc}}^{\mathrm{cell}}}{C_{\mathrm{uc}}}-\frac{U_C}{R_{\mathrm{uc}}^{\mathrm{laek}}{C}_{\mathrm{uc}}}---\left(9\right)$

${\stackrel{\·}{T}}_{\mathrm{uc}}=({\mathrm{\Φ}}_{\mathrm{uc}}^{\mathrm{cell}}-h{\mathrm{\Σ}}_{\mathrm{uc}}(T_{\mathrm{uc}}-T_{\mathrm{cool}}))/\left(m_u{c}_u\right)---\left(10\right)$

${\stackrel{\·}{\mathrm{SOC}}}_{\mathrm{uc}}=\frac{-I_{\mathrm{uc}}^{\mathrm{cell}}}{Q_{\mathrm{uc}}}---\left(11\right)$

Wherein, relevant to the drain current of ultracapacitor inside. h, ∑ _uc, T _cool, m _ucand c _ucwith the definition in formula (6) simultaneously, just object changes ultracapacitor into.Therefore ultracapacitor voltage can be expressed as:

$U_{\mathrm{uc}}=U_C-R_{\mathrm{uc}}^{\left(0\right)}{I}_{\mathrm{uc}}---\left(12\right)$

Electric capacity internal loss for:

${\mathrm{\Φ}}_{\mathrm{uc}}^{\mathrm{cell}}=\frac{{\left(U_C\right)}^2}{R_{\mathrm{uc}}^{\mathrm{leak}}}+R_{\mathrm{uc}}^{\left(0\right)}{\left(I_{\mathrm{uc}}^{\mathrm{cell}}\right)}^2+{\mathrm{\α}}_{\mathrm{uc}}{I}_{\mathrm{uc}}^{\mathrm{cell}}---\left(13\right)$

In formula (13) for the internal resistance of ultracapacitor, α _ucfor the internal loss factor of ultracapacitor.

Because ultracapacitor needs to carry out power back-off to storage battery when hybrid vehicle starts and accelerate, also want to reclaim braking energy fast, therefore DC/DC is two-way DC/DC changer, K in Fig. 4 simultaneously ₁and K ₂for power switch pipe, L _dcdcfor with resistive R _dcdcfilter inductance.If T _eopen the cycle for switching valve, D is dutycycle, works as K ₁during shutoff, K ₂at DT _eopen-minded in time; Equally, K is worked as ₁when opening, K ₂turn-off time be (1-D) T _e.The model of DC/DC is:

$L_{\mathrm{dcdc}}\frac{{\mathrm{dI}}_{\mathrm{uc}}}{\mathrm{dt}}=-R_{\mathrm{dcdc}}{I}_{\mathrm{uc}}+V_{\mathrm{uc}}-(1-D)U_b---\left(14\right)$

I _dcdc＝(1-D)I _uc(15)

The internal loss of same DC/DC is:

Φ _dcdc＝R _dcdcI _uc ²(16)

Finally, hybrid vehicle composite power source closed-centre system overall loss Φ _hesscan be expressed as:

Φ _hess＝Φ _b+Φ _uc+Φ _dcdc(17)

Because efficiency is not stackable, the efficiency of composite power source closed-centre system can investigate the efficiency of each parts.Optimization problem, for maximizing energy efficiency, namely minimizes the overall loss of hybrid power system, improves its efficiency, can be expressed as:

Objective function:

min(Φ _hess)＝min(Φ _b+Φ _uc+Φ _dcdc) (18)

Constraint condition: ${\stackrel{\·}{U}}_C=\frac{-U_C}{R_{\mathrm{uc}}^{\mathrm{leak}}{C}_{\mathrm{uc}}}-\frac{I_{\mathrm{uc}}}{N_{\mathrm{uc}}^{\left(p\right)}{C}_{\mathrm{uc}}}$

(1-β)U _b≤U _uc

β≤β _max＜1

$U_{\mathrm{uc}}\≤N_{\mathrm{uc}}^{\left(s\right)}{U}_{\mathrm{uc}}^{\mathrm{cell}-\max }$

$U_b\≤N_b^{\left(s\right)}{U}_b^{\mathrm{cell}-\max }$

$0\≤\left|I_b\right|\≤I_b^{\max }$

$0\≤\left|I_{\mathrm{uc}}\right|\≤I_{\mathrm{uc}}^{\max }$

Be necessary to make an explanation to constraint condition: first constraint condition represents bank of super capacitors internal voltage value (not considering internal resistance) from single order to the renewal on full rank; Second constraint condition defines the maximum voltage range of bank of super capacitors and the relation between accumulator battery voltage scope and bank of super capacitors voltage range, can find out, accumulator battery voltage is larger than bank of super capacitors voltage, and β is then the battery voltage range constraint factor; All the other constraint conditions give the boundary condition of Combined storage battery bank of super capacitors voltage and current.

In sum, energy efficiency of the present invention maximizes the hybrid vehicle composite power source under optimizing and is made up of storage battery, ultracapacitor and DC/DC changer, and ultracapacitor is in parallel with storage battery again after connecting with DC/DC changer.Model optimization method of the present invention, by setting up the math modeling of storage battery, ultracapacitor and DC/DC changer, solves the loss of modules, thus obtains the total power loss of hybrid power system.Induction and conclusion goes out the limiting condition of overall loss, obtains the maximized Optimized model of hybrid power system energy efficiency, because this Optimized model belongs to nonlinear programming category, adopts approximating programming method to solve.Objective function in Optimized model and constraint condition are approximately linear function, and the span of variable is limited, thus obtain an Approximate linear programming problem, then solve it by simplex method, it is met the last solution of optimal solution as optimization problem of initial condition.After optimizing, the watt loss of composite power source closed-centre system reduces greatly compared to before optimization, and energy utilization rate is improved.The operation point of storage battery and ultracapacitor high efficient area is increased, and distribute to obtain more crypto set simultaneously.

The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention.All any amendments done within the spirit and principles in the present invention, equivalent replacement and improvement etc., all should be included within protection scope of the present invention.

Claims (7)

1. energy efficiency maximizes the hybrid vehicle composite power source under optimizing, it is characterized in that: comprise storage battery, ultracapacitor and DC/DC changer, ultracapacitor is in parallel with storage battery again after connecting with DC/DC changer, storage battery as main power source, ultracapacitor and bidirectional DC-DC converter accessory feed in series.

2. energy efficiency maximizes the model optimization method of the hybrid vehicle composite power source under optimizing, and specifically comprises the steps:

1) math modeling of storage battery, ultracapacitor and DC/DC changer is set up;

2) solve step 1) in the loss of each model, thus obtain the total power loss of hybrid power system;

3) induction and conclusion goes out the limiting condition of overall loss, obtains the maximized Optimized model of hybrid power system energy efficiency; Because this Optimized model belongs to nonlinear programming category, approximating programming method is adopted to solve;

4) objective function in Optimized model and constraint condition are approximately linear function, and the span of variable is limited, obtain an Approximate linear programming problem, then solve it by simplex method, it is met the last solution of optimal solution as Optimized model of initial condition.

3. energy efficiency according to claim 2 maximizes the model optimization method of the hybrid vehicle composite power source under optimizing, it is characterized in that: described battery model is a dynamic system integrating four kinds of parameters, these four kinds of parameters comprise storage battery charge state SOC _b, surface temperature T _band relevant to internal capacitor two kinds of voltages ; Ultracapacitor model is by internal capacitor C _uc, shunt resistance and series resistance composition; DC/DC changer is two-way DC/DC changer, and structure is non-isolated half-bridge structure; Described Optimized model for objective function be:

min(Φ _hess)＝min(Φ _b+Φ _uc+Φ _dcdc) (1)

Wherein, Φ _hessfor hybrid vehicle composite power source closed-centre system overall loss; for the internal loss of storage battery; for the internal loss of ultracapacitor; Φ _dcdcfor the internal loss of DC/DC changer.

4. energy efficiency according to claim 3 maximizes the Optimized model of the hybrid vehicle composite power source under optimizing, and it is characterized in that: described storage battery is battery pack, by individual identical battery cell composition, for series connection number; for number of parallel;

Battery model is:

Wherein, for the electric current of cell; Cell resistance and electric capacity depend on SOC and the temperature of battery; Q _bfor battery rated storage capacity; m _bfor battery quality; c _bfor specific heat capacity; ∑ _bfor the exchange surface with cooling system; T _coolfor chilling temperature; H is coefficient of thermal conductivity; for inside battery loss;

The internal loss of storage battery for:

Wherein, for the internal resistance of battery; α _bfor inside battery dissipation factor.

5. energy efficiency according to claim 3 maximizes the Optimized model of the hybrid vehicle composite power source under optimizing, and it is characterized in that: described ultracapacitor by individual electric capacity monomer composition, for series connection number; for number of parallel;

Ultracapacitor model is:

Wherein, relevant to the drain current of ultracapacitor inside; for the electric current of monolithic capacitor; Q _ucfor rated capacitor memory capacity; m _ufor cond quality; c _ufor specific heat capacity; ∑ _ucfor the exchange surface with cooling system; T _coolfor chilling temperature; H is coefficient of thermal conductivity; T _ucfor surface temperature; U _cfor ultracapacitor builtin voltage, the electric capacity C of cond _ucdetermine U _csize; SOC _bfor cond state-of-charge; for capacitor internal loss;

The internal loss of ultracapacitor for:

Wherein, for the internal resistance of ultracapacitor; α _ucfor the internal loss factor of ultracapacitor.

6. energy efficiency according to claim 3 maximizes the Optimized model of the hybrid vehicle composite power source under optimizing, and it is characterized in that: described DC/DC changer is two-way DC/DC changer;

DC/DC changer model is:

I _dcdc＝(1-D)I _uc(12)

Wherein, L _dcdcfor with resistive R _dcdcfilter inductance; I _ucfor condenser current; U _ucfor condenser voltage; U _bfor accumulator battery voltage; D is dutycycle;

The internal loss Φ of DC/DC changer _dcdcfor:

Φ _dcdc＝R _dcdcI _uc ²(13)。

7. energy efficiency according to claim 2 maximizes the Optimized model of the hybrid vehicle composite power source under optimizing, and it is characterized in that: described constraint condition is:

(1-β)U _b≤U _uc(15)

β≤β _max＜1 (16)

Wherein, β is the battery voltage range constraint factor.