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CN105539423A - Hybrid vehicle torque distribution control method and system for protecting battery based on environment temperature - Google Patents

Hybrid vehicle torque distribution control method and system for protecting battery based on environment temperature Download PDF

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CN105539423A
CN105539423A CN 201510996693 CN201510996693A CN105539423A CN 105539423 A CN105539423 A CN 105539423A CN 201510996693 CN201510996693 CN 201510996693 CN 201510996693 A CN201510996693 A CN 201510996693A CN 105539423 A CN105539423 A CN 105539423A
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battery
torque
temperature
control
according
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CN 201510996693
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CN105539423B (en )
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陈龙
李文瑶
徐兴
汪少华
单海强
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江苏大学
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/06Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/08Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00Conjoint control of vehicle sub-units of different type or different function
    • B60W10/119Conjoint control of vehicle sub-units of different type or different function including control of all-wheel-driveline means, e.g. transfer gears or clutches for dividing torque between front and rear axle
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00Conjoint control of vehicle sub-units of different type or different function
    • B60W10/24Conjoint control of vehicle sub-units of different type or different function including control of energy storage means
    • B60W10/26Conjoint control of vehicle sub-units of different type or different function including control of energy storage means for electrical energy, e.g. batteries or capacitors
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W20/00Control systems specially adapted for hybrid vehicles
    • B60W20/10Controlling the power contribution of each of the prime movers to meet required power demand
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00Input parameters relating to a particular sub-units
    • B60W2510/24Energy storage means
    • B60W2510/242Energy storage means for electrical energy
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00Input parameters relating to a particular sub-units
    • B60W2510/24Energy storage means
    • B60W2510/242Energy storage means for electrical energy
    • B60W2510/246Temperature
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00Output or target parameters relating to a particular sub-units
    • B60W2710/06Combustion engines, Gas turbines
    • B60W2710/0666Engine torque
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00Output or target parameters relating to a particular sub-units
    • B60W2710/08Electric propulsion units
    • B60W2710/083Torque
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00Road transport of goods or passengers
    • Y02T10/60Other road transportation technologies with climate change mitigation effect
    • Y02T10/62Hybrid vehicles
    • Y02T10/6286Control systems for power distribution between ICE and other motor or motors

Abstract

The invention discloses a hybrid vehicle torque distribution control method and system for protecting a battery based on the environment temperature. The method comprises the steps that (1) environment temperature information of the area where a vehicle is located is collected; (2) the actual temperature of the battery is obtained through calculation according to the environment temperature information and a battery equivalent circuit model; the SoC value of the battery is obtained through calculation according to the dump battery energy and the maximum battery energy; (3) optimal control parameters are calculated through a neural network control method according to the SoC value and the actual temperature of the battery; (4) online minimum equivalent oil consumption strategy modeling is conducted, an objective function expression and a constrained formula of equivalent oil consumption are established, and the engine torque and the motor torque corresponding to the minimum oil consumption are worked out; and (5) torque distribution is conducted according to the obtained engine torque value and the motor torque value, and a control command is sent to drive the vehicle. Power is controlled to drive the system by considering the battery characteristics through the temperature, the battery protection function is achieved, and practical significance is achieved.

Description

结合环境温度保护电池的混合动力车转矩分配控制方法及系统 The hybrid torque distribution control method and system in conjunction with the ambient temperature of the battery protection

技术领域 FIELD

[0001]本发明涉及一种混合动力车电池保护的预测控制方法,特别涉及一种结合环境温度保护电池的混合动力车转矩分配控制方法及系统。 [0001] The present invention relates to a predictive control method of a hybrid battery protection, in particular, it relates to a hybrid torque distribution control method and system for temperature protection cell binding.

背景技术 Background technique

[0002 ]时代发展至今,相比传统的车辆用内燃机(ICE)和纯电动汽车(EV ),混合动力汽车可以在保证一定的续航里程前提下,实现更优的燃油经济性和污染排放性能。 [0002] era of development so far, compared to a conventional vehicle with an internal combustion engine (ICE) and electric vehicles (EV), hybrid vehicles can guarantee a certain mileage premise of achieving better fuel economy and emissions performance. 随着电力驱动关键技术进一步的发展,混合动力汽车中电力传动系统所占的比例日趋增加,比如:插电式混合动力汽车(PHEV ),而电池作为电力传动系统中的动力来源更是受到广泛的关注。 With the further development of electric drive key technologies, the proportion of hybrid vehicles in the increasing share of the electricity transmission system, such as: plug-in hybrid (PHEV), and battery as a power source of electric power transmission system is even more widespread s concern.

[0003] 能源管理控制与优化策略作为混合动力汽车研究的重要研究领域发展已久。 [0003] Energy management control and optimization strategies as a hybrid vehicle research development has long been an important area of ​​research. 早期能量管理控制使用启发式的方法,将所得的策略形式化为布尔或模糊规则,现如今这些方法仍然都在使用,并在最近的研究中得到改进。 Early energy management control using heuristic methods, the resulting strategy is formulated as a Boolean or fuzzy rules, now these methods are still in use, and improved in recent studies. 目前国内对这一领域的研究尚属起步阶段。 At present the domestic research in this area has just begun. 2013年,清华大学叶晓分析了动态规划法(DP),庞特亚金最小化原理(PMP)和等油耗最小化策略(ECMS)这几种能量管理策略,验证了ECMS能取得非常接近全局优化的燃油经济性。 2013, Tsinghua University YE analysis of dynamic programming (DP), Pang Teya gold minimization principle (PMP) such as fuel consumption and minimizing strategy (ECMS) these types of energy management strategies, demonstrate the ECMS can get very close to the global fuel economy optimization. 并于混合动力客车上验证了ECMS策略的可行性。 And on the hybrid buses verify the feasibility of ECMS strategy. 同年,吉林大学周文滨,采用模糊神经网络算法对发动机转矩和电机转矩进行优化分配,设计了基于模糊逻辑算法的能量控制策略。 In the same year, Jilin University Zhou Wenbin, fuzzy neural network algorithm for the engine torque and the motor torque to optimize distribution, design of energy control strategy based on fuzzy logic algorithm. 2015年,同济大学徐国庆等提出通过对交通信息的预测进行混合动力汽车转矩的最优分配。 2015, Tongji University, Xu Guoqing put forward the optimal allocation hybrid vehicle torque by predicting traffic information.

[0004] 电池是混合动力汽车动力来源的重要组成部分之一,过往混合动力汽车的能量管理策略研究中常常考虑电池电量余量而忽视温度的影响,故而以往的研究无法从整车控制策略调整上为处于低温或极高温环境下车辆的电池系统提供保护。 [0004] battery is an important component of the hybrid vehicle power sources of power, Energy Management Strategy of hybrid vehicles in the past often consider battery power while ignoring the influence of temperature margin and therefore previous studies can not control strategy adjustment from the vehicle in the protection of low or very high temperature environment of the vehicle battery system.

发明内容 SUMMARY

[0005] 为了解决上述问题,本发明提供了一种结合环境温度保护电池的混合动力车转矩分配控制方法及系统,以弥补现有控制方法在不同环境温度下对电池提供保护这一领域内的空白,根据不同的环境温度,在线实时调整混合动力车辆的电动机转矩,以实现控制电池负载,保护车辆电池的目的。 [0005] In order to solve the above problems, the present invention provides a hybrid torque distribution control method and system for binding Ambient temperature battery, to compensate for conventional control method of providing battery protection in this area at different ambient temperatures blank, depending on the ambient temperature, line real-time adjustment of the motor torque of the hybrid vehicle, in order to achieve control of the battery load, the vehicle battery protection purposes. 为实现上述目的,本发明采取以下技术方案: To achieve the above object, the present invention adopts the following technical scheme:

[0006] 结合环境温度保护电池的混合动力车转矩分配控制方法,包括如下步骤: [0006] The hybrid method combines the torque distribution control battery protection ambient temperature, comprising the steps of:

[0007] 1)采集车辆所处地区的环境温度信息; [0007] 1) collecting information about ambient temperature region in which the vehicle;

[0008] 2)根据环境温度信息以及电池等效电路模型,计算得到电池实际温度;由电池剩余电量和电池最大电量计算得到电池的SoC值; [0008] 2) The ambient temperature information and the equivalent circuit model of the battery, the battery is calculated to obtain an actual temperature; cells obtained from the calculated remaining battery capacity and the battery power SoC maximum value;

[0009] 3)根据所述SoC值和电池实际的温度,利用神经网络控制方法计算优化控制参数f; [0009] 3) the actual value of the temperature of the SoC and battery, a control method using a neural network calculates the optimal control parameters F;

[0010] 4)在线最小等效油耗策略建模,建立等效油耗的目标函数式和约束式,并求解出等效油耗最小时对应的发动机转矩和电动机转矩; [0010] 4) equivalent to the minimum fuel consumption line modeling strategy, to establish the equivalent fuel consumption objective function and constraints of formula, and solving the equivalent engine torque and the motor torque corresponding to a minimum fuel consumption;

[0011] 5)整车传动系及动力学模块按步骤4)得出的发动机转矩值和电动机转矩值进行转矩分配并发送控制命令驱动车辆。 [0011] 5) and the vehicle driveline dynamics module according to step 4) obtained values ​​of the engine torque and the motor torque value and the torque distribution transmitted vehicle drive control command.

[0012] 作为优选,步骤1)中采集环境温度的方法是通过天气预测软件实现的,所述天气软件包括:手机天气预报软件,车载电脑天气模块软件,GPS导航装置中天气预报软件。 [0012] Advantageously, the method step 1) is collected ambient temperature achieved by the weather forecast software, the weather software comprising: software phone weather forecast, weather board computer software module, GPS navigation device weather forecasting software.

[0013] 作为优选,步骤2)中计算电池实际温度的表达式为: [0013] Calculation of the actual temperature of the battery 2) Preferably, the step expression is:

[0014] [0014]

Figure CN105539423AD00061

[0015] 式中,I代表电池电流,R,R〇分别为电池等效电路中串联和并联的电阻值,Tbody是电池实际温度,Tamb是环境温度,m。 [0015] In the formula, I representative of battery current, R, and the series resistance were R〇 value of the parallel equivalent circuit of the battery, Tbody actual battery temperature, Tamb is the ambient temperature, m. 是单个电池热容量,hA是散热系数。 Is the heat capacity of a single cell, hA is the radiation coefficient.

[0016] 作为优选,步骤2)中计算电池SoC值的表达式为: [0016] Advantageously, the battery SoC value calculated in step 2) expression:

[0017] [0017]

Figure CN105539423AD00062

[0018] 式中,Qmax是电池的最大电量,Q(t)是电池t时刻剩余的电量,Ι(τ)是单位时间电池电流。 [0018] where, Qmax is the maximum battery power, Q (t) at time t is a battery power remaining, Ι (τ) is the current per unit time of the battery.

[0019] 作为优选,步骤3)中所述的神经网络采用单一神经元控制结构;所述步骤3)的实现具体包括如下步骤: [0019] Advantageously, in step 3) said neural network control structure of a single neuron; step 3) is implemented comprises the following steps:

[0020] 3-1),计算神经网络的两个输入量:xi(SoC)和X2(temp); [0020] 3-1), two inputs of the neural network calculation: xi (SoC) and X2 (temp);

[0021 ] 3-2),依据3-1)中的两个输入量计算得到优化控制参数f = XI (SoC) · wi+X2 (temp) · W2〇 [0021] 3-2), based on two inputs 3-1) calculated in the optimized control parameter f = XI (SoC) · wi + X2 (temp) · W2〇

[0022] 作为优选,所述步骤3-1)中计算ή (SoC)的过程包括: [0022] Advantageously, during said step 3-1) is calculated ή (SoC) comprising:

[0023] a,将从电池管理系统中读取的电池SoC值按式 [0023] a, from the value of the battery cell management system SoC read by the formula

Figure CN105539423AD00063

吐理得到xsoc,并使xsoc介于区间[_1,1];其中,SoC代表电池剩余容量值,也称电池荷电状态, SoCh代表最高的电池剩余容量值,s〇a代表最低的电池剩余容量值; Xsoc jetting treatment to give, and the interval between xsoc [selected, 1]; wherein, SoC representative of the battery remaining capacity value, also known as the state of charge of the battery, SOCH represents the highest remaining battery capacity value that represents the lowest remaining battery s〇a capacity value;

[0024] b,构造函数5 ,并使X1 (SoC)介于区间[0,1 ]; [0024] b, constructors 5, and X1 (SoC) between the interval [0,1];

[0025] 所述步骤3-1)中计算X2 (temp)的过程包括: During [0025] the step 3-1) is calculated X2 (temp) comprises:

[0026] c,通过实验获得电池容量随电池实际温度变化的特性函数f (temp); [0026] c, experimentally obtained by the actual battery capacity with the battery temperature change characteristic function f (temp);

[0027] d,对函数值f (temp)按式A㈦叩)=二―):进行归一化处理,得到作为人工神经网络的第二个输入值X2(temp),并使X2(temp)的值介于区间[0,1 ]。 [0027] d, the value of the function f (temp) A㈦ knock by formula) = diethylene -): normalized to give a second input value X2 (temp) as an artificial neural network, and X2 (temp) values ​​between the interval [0,1].

[0028] 作为优选,所述步骤3-2)中的wi = 0.5,W2 = 0.5。 [0028] Advantageously, the step 3-2) in wi = 0.5, W2 = 0.5.

[0029] 作为优选,步骤4)中建立的目标函数式为: [0029] Advantageously, step 4) established objective function is:

[0030] [0030]

Figure CN105539423AD00064

,

[0031] 建立的约束式为: [0031] constraints established formula:

[0032] [0032]

Figure CN105539423AD00071

[0033] 其中,J(t)是表示整车等效燃油消耗量的目标函数,木,(T)表示瞬时等效燃油消耗量,miM (τ)是发动机所消耗的燃料,me* (τ)和mge3ne3 (τ)分别是电动机和发电机的等效燃油消耗,Τ和ω分别代表转矩和转速,i表不发动机,电动机和发电机中的一种。 [0033] wherein, J (t) is a function of the equivalent target vehicle fuel consumption, wood, (T) represents the instantaneous consumption of equivalent fuel, miM (τ) is the fuel consumed by the engine, me * (τ ) and mge3ne3 (τ) are the equivalent fuel consumption of a motor and a generator, and ω Τ represent torque and speed, table I a non-engine, a motor and a generator. Timin( ω i)表不最小转矩,T严χ(ωι)表示最大转矩,«表示最小转速,ωΓ"表示最大转速。SoC为电池剩余电量,SoCmin表示最小电池剩余容量,S〇Cm ax表示最大电池剩余容量,Pbatt(t)电池t时刻的功率,表示电池最小功率,乃=表示电池最大功率。 Timin (ω i) no minimum torque table, T Yan χ (ωι) represents the maximum torque, «represents a minimum speed, ωΓ" denotes a maximum speed for the battery residual quantity .SoC, SOCmin represents a minimum remaining battery capacity, S〇Cm ax denotes a maximum remaining battery capacity, Pbatt (t) at time t of the battery power, the battery minimum power, maximum power is the battery = represents.

[0034] 作为优选,所述步骤4)还包括建立电动机等效燃油消耗函数式: [0034] Advantageously, said step 4) further comprises establishing a motor function equivalent fuel consumption formula:

[0035] [0035]

Figure CN105539423AD00072

[0036] 其中,y J + 因数γ取值依赖于电动机工作状态,qch和qdch分别为电动2 机充、放电过程中电动机的能量转化效率,Tm和ω 别是电动机的转矩和转速,f是优化控制参数,获得,Qlhv代表低热值; [0036] wherein, y J + γ factor dependent on the value of the motor operation state, and Qch are qdch filling machine motor 2, the energy conversion efficiency of the motor during discharge, Tm and ω are respectively the motor torque and speed, f is to optimize the control parameters, is obtained, Qlhv representative of low calorific value;

[0037] 还包括建立发动机转矩函数式:Treq = Tm+Tice,其中Treq是通过加速踏板信号得到的当前需求转矩。 [0037] further comprises establishing the engine torque is a function of the formula: Treq = Tm + Tice, Treq which is obtained by the torque demand signal for the current accelerator pedal.

[0038] 本发明还提出了结合环境温度保护电池的混合动力车转矩分配控制系统,包括温度信息采集模块、电池参数计算模块、控制处理模块以及传动系及动力学模块;所述温度信息采集模块连接电池参数计算模块,所述电池参数计算模块连接控制处理模块,所述控制处理模块与所述传动系及动力学模块之间互连; [0038] The present invention also provides a torque distribution control system in conjunction with a hybrid ambient temperature protection cell comprising temperature information acquisition module, a battery parameter calculation module, the processing module and the control and drive train dynamics module; the temperature information acquisition connection parameter calculation module battery module, the battery module is connected to a control parameter calculation processing module, said control module and the interconnection between the processing and drive train dynamics module;

[0039] 所述温度信息采集模块用于采集车辆所处环境的温度、并将环境的温度值送给所述电池参数计算模块,所述温度信息采集模块通过天气软件实现; [0039] The temperature of the temperature of the vehicle information collecting means for collecting the environment, and the ambient temperature value to said parameter calculation module battery, the temperature information acquisition module implemented by software weather;

[0040] 所述电池参数计算模块包括电池实际温度计算模型和电池余量估算模型,所述电池实际温度计算模型用于得到电池实际温度,电池余量估算模型用于得到电池余量值,所述电池参数计算模块将得到的电池实际温度和电池余量值送给所述控制处理模块; [0040] The battery module includes a battery parameter calculating temperature calculation model and the actual battery remaining amount estimation model, the battery model is used to calculate the actual temperature of the obtained actual battery temperature, the battery remaining estimation models for obtaining a battery remaining amount value, the actual battery temperature and the battery remaining amount value of said battery parameter calculation module to said obtained control processing module;

[0041] 所述控制处理模块包括优化控制参数处理模块和转矩分配控制优化模型模块;所述优化控制参数处理模块采用人工神经网络控制结构,用于对所述电池实际温度和电池余量值进行处理得到优化控制参数f,所述转矩分配控制优化模型模块的作用是利用f的值结合建立的等效油耗目标函数得到发动机转矩和电动机转矩值,所述控制处理模块将得到发动机转矩和电动机转矩值送给所述传动系及动力学模块; [0041] The control processing module comprises a processing module and a control parameter optimizing torque distribution control model optimization module; the control parameter optimization process module artificial neural network control structure, the actual temperature of the battery and the battery remaining amount value process control parameters optimized for f, the torque distribution control function is optimized model module with an equivalent fuel consumption objective function value f is obtained to establish binding engine torque and the motor torque values, the engine operation control processing module and motor torque value and to said drive train dynamics module;

[0042] 所述传动系及动力学模块根据发动机转矩和电动机转矩值进行转矩分配以及驱动车辆。 The [0042] Kinetic and driveline torque distribution module according to the engine torque and the motor torque value and the vehicle is driven.

[0043]本发明的有益效果: [0043] Advantageous effects of the invention:

[0044] 1)随着智能手机,各种天气预报软件的发展,利用天气软件,采集车辆所处环境的实时温度信息更加方便。 [0044] 1) As smart phones, all kinds of weather forecasting software development, the use of weather software, collecting real-time temperature environment in which the vehicle information more convenient.

[0045] 2)改进等效油耗最小化策略模型,设计受环境温度影响的控制参数,使混合动力汽车电动机和电池工作模式受温度变化调整成为可能。 [0045] 2) Improved Equivalent Policy Model minimize fuel consumption, the design control parameters influenced by ambient temperature of the hybrid vehicle and an electric motor mode of operation of the battery temperature adjustment becomes possible.

[0046] 3)提出了利用人工神经网络控制理论,量化计算温度和SoC荷电量,并建立规则求解控制参数f。 [0046] 3) proposed the use of artificial neural network control theory, calculate the quantization SoC temperature and the charged amount, and to create a rule for solving control parameter f. 为优化后的等油耗最小化策略模型提供了一种确定优化控制参数f的方法实例。 Provides a method of determining optimal control parameter f, etc. Examples of a method of minimizing fuel consumption optimization policy model.

[0047] 4)实际使用过程中通过加入温度对电池特性的考虑,控制电力驱动系统的使用份额,起到保护电池和延长电池寿命的作用。 [0047] 4) by adding the actual process temperature consideration of the battery characteristics, share control using the electric drive system so as to protect the battery and battery life prolonged action. 通过实时温度气象信息的导入,使优化更具实际意义。 By introducing real-time temperature of meteorological information, the optimizer more meaningful.

附图说明 BRIEF DESCRIPTION

[0048]图1是某插电式混合动力SUV传动系结构示意图。 [0048] FIG. 1 is a schematic diagram of a plug-in hybrid SUV driveline structure.

[0049] 图2是电池等效电路图; [0049] FIG. 2 is an equivalent circuit diagram of a battery;

[0050] 图3是单个人工神经网络算法示意图。 [0050] FIG. 3 is a schematic view of a single artificial neural network algorithm.

[0051 ]图4是基于环境温度信息的混合动力车电池保护的转矩分配控制原理框图。 [0051] FIG. 4 is a schematic block diagram of the torque distribution based on the hybrid battery protection control of environmental temperature information.

[0052]图5是是等油耗最小策略实施算法逻辑图。 [0052] FIG. 5 is the minimum fuel consumption are equally embodiment arithmetic logic policy FIG.

[0053]图6是某磷酸铁锂电池容量随温度变化特性图。 [0053] FIG. 6 is a lithium iron phosphate capacity with temperature change characteristic of FIG.

具体实施方式 detailed description

[0054]下面结合附图和具体实施例对本发明作进一步描述。 [0054] conjunction with the accompanying drawings and the following specific embodiments of the present invention will be further described.

[0055] 图1所示为某款插电式混合动力的传动系结构示意图,采用发动机前驱电机后驱的四驱多功能运动车(SUV)结构形式,发动机经过变矩器和变速箱通过半轴驱动前轮;后电机由电池供电,通过齿轮组减速增扭后驱动后轮;前发电机由发动机带动给电池充电;与此同时,后电机可在制动过程中进行制动能量回收,给电池充电。 [0055] FIG. 1 shows a schematic view of a drive train plug-in hybrid structure for a section, the structure using four-wheel drive motor driving the engine precursor sports utility vehicle (SUV), the engine via a torque converter and the transmission by half front-wheel drive shaft; the motor is powered by batteries, by twisting the reduction gear train by a drive wheel; before the generator is driven by the engine to charge the battery; at the same time, the motor can be braked during braking energy recovery, to charge the battery.

[0056] 本发明以这款插电式混合动力车等油耗最小化策略控制系统为例进行说明,本发明提出的转矩分配控制原理框图如图4所示,包括温度信息采集模块、电池参数计算模块、 控制处理模块以及传动系及动力学模块;所述温度信息采集模块连接电池参数计算模块, 所述电池参数计算模块连接控制处理模块,所述控制处理模块与所述传动系及动力学模块之间互连;所述温度信息采集模块用于采集车辆所处环境的温度、并将环境的温度值送给所述电池参数计算模块,所述温度信息采集模块通过天气预测软件实现;所述电池参数计算模块包括电池实际温度计算模型和电池余量估算模型,所述电池实际温度计算模型用于得到电池实际温度,电池余量估算模型用于得到电池余量值,所述电池参数计算模块将得到的电池实际温度和电池余量值送给所述控制处理模块 [0056] In the present invention this and other plug-in hybrid fuel minimization strategies control system as an example, the present invention proposes torque distribution control block diagram shown in Figure 4, includes a temperature information acquisition module, battery parameters calculation module, the processing module and the control and drive train dynamics module; the temperature information acquisition module parameter calculation module connected to the battery, the battery control parameter calculation module connected to the processing module, the processing module and the control and drive train dynamics interconnection between modules; the temperature information collection module for collecting the temperature of the environment of the vehicle, and the ambient temperature of the battery to the parameter calculation module, the temperature information acquisition module implemented by software, weather forecasts; the said battery parameter calculation module includes a battery temperature calculation model and the actual battery remaining amount estimation model, the battery model is used to calculate the actual temperature of the obtained actual battery temperature, the battery remaining estimation models for obtaining remaining battery value, the battery parameter calculation actual battery temperature and the battery remaining amount value obtained to said module control processing module ;所述控制处理模块包括优化控制参数处理模块和转矩分配控制优化模型模块;所述优化控制参数处理模块采用人工神经网络控制结构,用于对所述电池实际温度和电池余量值进行处理得到优化控制参数f,所述转矩分配控制优化模型模块的作用是利用f的值,结合建立的等效油耗目标函数得到发动机转矩值和电动机转矩值,所述控制处理模块将得到发动机转矩值和电动机转矩值送给所述传动系及动力学模块;所述传动系及动力学模块根据发动机转矩值和电动机转矩值进行转矩分配以驱动车辆。 ; Said control processing module comprises a processing module and a control parameter optimizing torque distribution control model optimization module; the control parameter optimization process module artificial neural network control structure for the battery cell and the actual temperature of the processed values ​​I optimized control parameter f, the torque distribution control function is optimized model module with the value of f, the target binding function of the equivalent fuel consumption of the engine torque obtained established value and the motor torque values, the engine operation control processing module torque value and the torque value to said motor and drive train dynamics module; and dynamics of the drive train torque distribution module according to the engine torque value and the motor torque value to drive the vehicle.

[0057] 与此同时,本发明还提出了基于图4所示系统的转矩分配控制方法,包括:第一步为环境温度信息采集,第二步为电池特性参数计算,第三步为采用神经网络控制方法计算优化控制参数,第四步为在线等效油耗最小控制策略建模,第五步为输出发动机和电动机的转矩分配。 [0057] Meanwhile, the present invention also provides a method of controlling torque distribution system based on FIG. 4, comprising: a first step of collecting information on the ambient temperature, the second step is calculated as the cell characteristics, the third step is employed neural network control method calculates the optimal control parameters, a fourth step of the minimum fuel control strategy line equivalent model, the output distribution of the engine torque and a motor for the fifth step. 具体实现如下所述: The specific implementation is as follows:

[0058] 步骤1)环境温度信息采集:由天气预测软件连线当地气象观测部门采集和存储车辆所处地区的环境温度信息。 [0058] Step 1) ambient temperature information collection: the connection ambient temperature information on the regional meteorological observation local authorities collect and store the vehicle by the weather forecasting software. 包括:手机天气预报软件,车载电脑天气模块软件,GPS导航装置中天气预报软件等。 Including: mobile phone weather forecast software, the weather module onboard computer software, GPS navigation device in weather forecasting software.

[0059] 步骤2)电池特性参数计算:由车辆电池管理系统读取实时的环境温度信息,结合电池等效电路模型(如图2所示),按式(1)计算得到电池实际温度Tbody。 [0059] Step 2) calculated cell parameters: real-time information read by the ambient temperature of the vehicle battery management system, in conjunction with a battery equivalent circuit model (shown in Figure 2), calculated according to formula (1) obtained actual battery temperature Tbody. 同时,由电池剩余电量和电池最大电量计算得到电池的SoC值。 Meanwhile, SoC calculated values ​​obtained by the remaining battery amount and the maximum capacity of the battery cell.

Figure CN105539423AD00091

[0060] (1) [0060] (1)

[0061] (2) [0061] (2)

[0062] 式(1)中,I代表电池电流,R,R〇分别为图2所示电池等效电路中串联和并联的电阻值,Tbody是电池实际温度,Tamb是环境温度,nk是单个电池热容量,hA是散热系数。 [0062] Formula (1), I representative of battery current, R, R〇 resistance values ​​are connected in parallel and in series to a battery equivalent circuit shown in FIG. 2, Tbody actual battery temperature, Tamb is the ambient temperature, nk single heat capacity of the battery, hA is the radiation coefficient.

[0063] 式(2)中,Qmax是电池的最大电量,Q(t)是电池t时刻剩余的电量,I (τ)是单位时间电池电流。 [0063] Formula (2), Qmax is the maximum battery power, Q (t) at time t is the remaining battery power, I (τ) is the current per unit time of the battery.

[0064] 步骤3)采用神经网络控制方法计算优化控制参数:为结合电池SoC值和电池实际温度两项参数,综合确定电动机所应分配到的转矩,本发明使用神经网络控制方法来确定目标函数中的优化控制参数f。 [0064] Step 3) neural network method of calculating the control parameters are optimized: the battery SoC binds actual temperature value and the battery two parameters, the torque of the motor is determined to be integrated is assigned to, and the present invention is a control method using a neural network to determine the target Optimal control parameter function f. 由于输入量较少,故采用单一神经元控制结构(如图3所示), 有利于控制实施的效率。 Due to less input, so the use of a single neuron control structure (Figure 3), facilitates the control of the efficiency of the implementation. 为此首先求解神经网络的两个输入量:X1(S〇C)和X2(temp)。 Two inputs of Neural Networks do this first: X1 (S〇C) and X2 (temp).

Figure CN105539423AD00092

[0065] 从电池管理系统中读取计算得到的电池的SoC值,按式(3)进行处理,使中间处理值xsoc介于区间[_1,1];为满足在SoC低值下惩罚(减少)电力驱动系统,在SoC高值下激励电力驱动系统,按式(4)构造函数^(5〇〇,使人工神经网络的第一个输入值X1(S〇C)介于区间[0,1]。 [0065] read from the battery management system SoC of the battery is calculated, the process according to equation (3), so that the interval between the intermediate processing value xsoc [selected, 1]; SoC to meet the low penalty (reduction ) electric drive system, the excitation electric drive system SoC at a high value, according to equation (4) constructor ^ (5〇〇 the first artificial neural network input value X1 (S〇C) between the interval [0, 1].

[0066] (3:): [0066] (3 :):

[0067] (4) [0067] (4)

[0068] 式(3) - (4)中,SoC代表电池剩余容量值,也称电池荷电状态,SoCh代表最高的电池剩余容量值,s〇a代表最低的电池剩余容量值。 [0068] Formula (3) - (4), SoC representative of the battery remaining capacity value, also known as the state of charge of the battery, SOCH represents the highest remaining battery capacity value that represents s〇a lowest remaining battery capacity value.

[0069]人工神经网络的第二个输入值x2(temp),是与电池实际温度相关的一个函数输入。 [0069] The second artificial neural network input value x2 (temp), is a function of the input cell associated with the actual temperature. 主要来源于实际使用车载电池的实验数据。 Mainly from actual experimental data using vehicle battery. 通过实验可以获得电池容量随电池实际温度变化的特性函数f (temp),如图6所示为实验测得的某磷酸铁锂电池特性,a)为-20°C_25 °C时电池容量随电池实际温度变化的曲线;b)为25°C_60°C时电池容量随电池实际温度变化的曲线。 Battery capacity can be obtained through experiments with actual battery temperature characteristic function f (temp), shown in Figure 6 for a lithium iron phosphate experimentally measured characteristics, a) is -20 ° C_25 ° C with the battery capacity of the battery the actual temperature curve; b) the actual capacity of the battery with the battery temperature curve of 25 ° C_60 ° C. f (temp)反应了随着温度变化电池特性实际发生的变化,函数值越高说明电池特性越理想,当电池特性理想时激励电力驱动系统,否则惩罚(减少)其使用。 f (temp) the reaction temperature with a change in the actual characteristics of the battery, the higher the value of the function over the battery characteristics, the excitation power characteristic of the drive system when the battery is over, otherwise penalty (decrease) its use. 对函数值f (temp)按式(6)进行归一化处理,得到作为人工神经网络的第二个输入值x2(temp),介于区间[0,1]。 A function value f (temp) for the normalization process by the formula (6), as the input values ​​to obtain a second artificial neural network x2 (temp), between the interval [0,1].

[0070] Λ2{ίίΐ!Ψ) - f U v 77~~:- [0070] Λ2 {ίίΐ Ψ) - f U v 77 ~~:! -

[0071] 最后以式(7)定义人工神经网络的求解法则,由于输入的两个影响因素属于并列特性,定义权重系数wi=W2 = 0.5,得到优化控制参数f,并且f的值介于[0,1 ]区间。 [0071] Finally, formula (7) defines the rules for solving artificial neural network, because of two factors belonging to parallel input characteristics defined weighting coefficients wi = W2 = 0.5, optimized control parameter f, and f a value between [ 0,1].

[0072] f = xi(SoC) · wi+X2(temp) · W2 (7) [0072] f = xi (SoC) · wi + X2 (temp) · W2 (7)

[0073] 步骤4)在线最小等效油耗策略(online-ECMS)目标建模:在线等效油耗控制器实施策略及与整车连接示意图如图5所示,在线等效油耗控制器从整车读取当前的需求转矩, 以需求转矩与最大电机转矩为上限,对电机转矩按油耗最小目标进行寻优,最后向整车输出优化得到的电机转矩和发动机转矩。 [0073] Step 4) equivalent to the minimum fuel consumption line policy (online-ECMS) modeling objectives: equivalent fuel line connected to the controller and strategies embodiment shown in Figure 5 a schematic view of the vehicle, from the vehicle controller fuel line equivalent You need to read the current torque demand with the maximum torque limit for the motor torque, the motor torque target optimization according to minimize fuel consumption, the engine torque and the motor torque obtained last vehicle to optimize output.

[0074]在线等效油耗策略的主要目标是找到以等效油耗最小为目标求解得出优化转矩分配(包括发动机转矩和电动机转矩),同时满足一些等式和不等式约束。 [0074] The main objective of the strategy is the online equivalent fuel consumption of equivalent fuel consumption in order to find the minimum target Solving for optimized torque distribution (including the engine and motor torque), while meeting some of the equality and inequality constraints. 结合等效油耗最小化策略模型,获得此系统在线等效油耗最小策略的目标函数式(8)和约束式(9)。 Binding model of the equivalent fuel consumption minimization strategies, the system online to obtain the target functional equivalent of the minimum fuel consumption policy (8) and the constraints of formula (9).

[0075] [0075]

Figure CN105539423AD00101

(8) (8)

[0 (9): [0 (9):

[0077]式(8)-(9)中,J(t)是表示整车等效燃油消耗量的目标函数,表示瞬时等效燃油消耗量,lilies (τ)是发动机所消耗的燃料,man (T)和mge3ne3 (τ)分别是电动机和发电机的等效燃油消耗,Τ和ω分别代表转矩和转速,i表不发动机,电动机和发电机中的一种。 [0077] Formula (8) - (9), J (t) is a function of the equivalent target vehicle fuel consumption, equivalent represents the instantaneous fuel consumption, lilies (τ) is the fuel consumed by the engine, man (T) and mge3ne3 (τ) are the equivalent fuel consumption of a motor and a generator, and ω Τ represent torque and speed, table I a non-engine, a motor and a generator. Timin (表示最小转矩,Timax( c〇i)表示最大转矩,©广表示最小转速,6>;^表示最大转速。SoC为电池剩余电量,SoCmin表示最小电池剩余容量,S〇Cm ax表示最大电池剩余容量,Pbatt( t )电池t 时刻的功率,P:1表示电池最小功率,表示电池最大功率。 TiMin (indicates minimum torque, Timax (c〇i) represents the maximum torque, minimum speed © represents a wide, 6>; ^ represents the maximum rotation speed of battery residual quantity .SoC, SOCmin represents a minimum remaining battery capacity, ax represents S〇Cm maximum remaining battery capacity, Pbatt (t) at time t of the battery power, P: 1 represents the minimum battery power, the maximum power that the battery.

Figure CN105539423AD00102

[0078] 其中,电动机的等效燃油消耗的函数式(10)如下: [0078] wherein the equivalent fuel consumption of the motor function of formula (10) as follows:

[0079] .(10:) [0079]. (10 :)

[0080] (11) [0080] (11)

[0081 ]式中,r^h和ndch分别为充放电过程中电动机的能量转化效率,Tm和ω m是电动机的转矩和转速,f是步骤3)得到的优化控制参数,Quw代表低热值。 [0081] In the formula, r ^ h and energy conversion efficiency were ndch during charging and discharging of the motor, Tm, and ω m is the motor torque and speed, f is step 3) optimal control parameters obtained, Quw representative of low calorific value . 因数γ取值依赖于电动机工作状态,如在制动能量回收时的充电状态,即电力将储存于电池中而不被使用,等效燃油消耗为负,正常驱动时油耗为正。 The value depends on the factor γ motor operating state, charging state when the braking energy recovery, i.e., the power stored in the battery is not used, the equivalent fuel consumption is negative, the normal consumption is driven positive.

[0082]发电机由于只起充电作用,所以等效燃油消耗的函数如式(5)所示,始终为负。 [0082] Since the generator only play the role of charge, so the equivalent fuel consumption as a function of the formula (5), is always negative.

[0083] [0083]

Figure CN105539423AD00111

(⑵ (⑵

[0084] 式(12)中,为发电机效率,Tg_和cog_为发电机的转矩和转速。 In the [0084] Formula (12), the generator efficiency, Tg_ and cog_ torque and rotational speed of the generator.

[0085] 以上述的四驱结构为例,通过加速踏板信号等可得到当前的需求转矩Treq,需求转矩分配给电动机的转矩T4P发动机的转矩满足式(13)。 [0085] In the above structure as an example of the four-wheel drive, torque Treq obtained by the current demand signals, an accelerator pedal, the torque distributed to satisfy the required torque of formula (13) T4P engine torque of the motor.

[0086] Treq = Tm+Tice (13) [0086] Treq = Tm + Tice (13)

[0087] 进一步由式子(13)可以求出发动机转矩Tice。 [0087] Further by using equation (13) can be calculated engine torque Tice.

[0088] 步骤5)整车传动系及动力学模块按步骤4)得出的发动机转矩值和电动机转矩值进行转矩分配并发送控制命令驱动车辆。 [0088] Step 5) and the vehicle driveline dynamics module according to step 4) obtained values ​​of the engine torque and the motor torque value and the torque distribution transmitted vehicle drive control command.

[0089] 本发明同样适用于其他串联式、并联式和混联式的混合动力汽车能源管理控制系统,具体建模方法与控制过程与本文所述混合动力汽车等油耗最小化策略控制系统一致, 在此不再重复描述。 [0089] The present invention is equally applicable to other serial, parallel and hybrid serial consistent hybrid vehicle energy management control systems, particularly modeling and control procedures and the like herein, the hybrid vehicle control system strategy to minimize fuel consumption, description will not be repeated.

[0090] 以上所述仅仅用于描述本发明的技术方案,并不用于限定本发明的保护范围,应当理解,在不违背本发明实质内容和原则的前提下,所作任何修改、等同替换等都将落入本发明的保护范围内。 [0090] The above description is used merely aspect of the present invention is not intended to limit the scope of the present invention, it should be understood that without departing from the spirit and principles of the present invention, the content of the premise, any changes made, so equivalents It will fall within the scope of the present invention.

Claims (10)

  1. 1. 结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,包括如下步骤: 1) 采集车辆所处地区的环境溫度信息; 2) 根据环境溫度信息W及电池等效电路模型,计算得到电池实际溫度;由电池剩余电量和电池最大电量计算得到电池的SoC值; 3) 根据所述SoC值和电池实际的溫度,利用神经网络控制方法计算优化控制参数f; 4) 在线最小等效油耗策略建模,建立等效油耗的目标函数式和约束式,并求解出等效油耗最小时对应的发动机转矩和电动机转矩; 5) 整车传动系及动力学模块按步骤4)得出的发动机转矩值和电动机转矩值进行转矩分配并发送控制命令驱动车辆。 Torque distribution control method of a hybrid vehicle in conjunction with a battery protection ambient temperature, characterized by comprising the following steps: 1) collecting information about ambient temperature region in which the vehicle; 2) according to the ambient temperature information and the equivalent circuit model of the battery W , the actual temperature of the battery is calculated; cells obtained from the calculated remaining battery capacity and the battery power SoC maximum value; 3) based on the actual value of the temperature of the SoC and battery, calculating optimal control parameters f control method using a neural network; minimum 4) online modeling strategy equivalent fuel consumption, fuel consumption goal of establishing an equivalent function and constraints type, and solving the equivalent engine torque and the motor torque corresponding to a minimum fuel consumption; 5) and the vehicle driveline dynamics module according to step 4 ) derived from an engine torque value and the motor torque value and the torque distribution transmitted vehicle drive control command.
  2. 2. 根据权利要求1所述的结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,步骤1)中采集环境溫度的方法是通过天气预测软件实现的,所述天气软件包括: 手机天气预报软件,车载电脑天气模块软件,GPS导航装置中天气预报软件。 The hybrid method combines the torque distribution control the ambient temperature of the battery protection as claimed in claim 1, characterized in that, in method step 1) collecting ambient temperature is achieved by the weather prediction software, the software includes weather : Mobile weather forecast software, the weather module onboard computer software, GPS navigation device in weather forecasting software.
  3. 3. 根据权利要求1所述的结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,步骤2)中计算电池实际溫度的表达式为: The hybrid method combines the torque distribution control the ambient temperature of the battery protection claimed in claim 1, wherein in step 2) the actual battery temperature calculated in the expression:
    Figure CN105539423AC00021
    式中,I代表电池电流,R,Ro分别为电池等效电路中串联和并联的电阻值,T b。 Wherein, I representative of battery current, R, Ro, respectively parallel and series resistance in the equivalent circuit for the battery, T b. dy是电池实际溫度,Tamb是环境溫度,me是单个电池热容量,hA是散热系数。 dy is the actual battery temperature, Tamb is the ambient temperature, me is the heat capacity of a single cell, hA is the radiation coefficient.
  4. 4. 根据权利要求1所述的结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,步骤2)中计算电池SoC值的表达式为: The hybrid method combines the torque distribution control the ambient temperature of the battery protection claimed in claim 1, wherein the battery SoC value calculated in step 2) is expressed as:
    Figure CN105539423AC00022
    式中,Qmax是电池的最大电量,Q(t)是电池t时刻剩余的电量,Ι(τ)是单位时间电池电流。 Where, Qmax is the maximum battery power, Q (t) at time t is a battery power remaining, Ι (τ) is the current per unit time of the battery.
  5. 5. 根据权利要求1所述的结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,步骤3)中所述的神经网络采用单一神经元控制结构;所述步骤3)的实现具体包括如下步骤: 3-1),计算神经网络的两个输入量:xi(SoC)和X2(temp); 3-2),依据3-1)中的两个输入量计算得到优化控制参数f = xi(SoC) -wi+X2(temp) ·Κ2。 The hybrid method combines the torque distribution control the ambient temperature of the battery protection claimed in claim 1, wherein in step 3) said neural network control structure of a single neuron; step 3) implemented includes the following steps: 3-1), two inputs of the neural network calculation: xi (SoC) and X2 (temp); 3-2), based on two inputs 3-1) calculated optimal control parameter f = xi (SoC) -wi + X2 (temp) · Κ2.
  6. 6. 根据权利要求5所述的结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,所述步骤3-1)中计算XI (SoC)的过程包括: 曰,将从电池管理系统中读取的电池SoC值按式 The hybrid method combines the torque distribution control Ambient temperature battery according to claim 5, wherein, during said step 3-1) is calculated XI (SoC) comprising: said, from the battery battery management system SoC values ​​read by the formula
    Figure CN105539423AC00023
    江理得到xsoc,并使xsoc介于区间[-1,1 ];其中,SoC代表电池剩余容量值,也称电池荷电状态,So姑代表最高的电池剩余容量值,SoCl代表最低的电池剩余容量值; b,构造函1 Jiang Li xsoc obtained, and xsoc between the interval [-1,1]; wherein, SoC representative of the battery remaining capacity value, also known as the state of charge of the battery, So regardless of the remaining battery capacity represents the highest value, representing the lowest remaining battery SOCL capacity value; b, constructors 1
    Figure CN105539423AC00024
    并使xi(SoC)介于区间[0,1]; 所述步骤3-1)中计算X2( temp)的过程包括: C,通过实验获得电池容量随电池实际溫度变化的特性函数f (temp); d,对函数值f (temp)按式 And xi (SoC) between the interval [0,1]; 3-1) calculated in the step X2 (temp) of the process comprises: C, battery capacity characteristic obtained by the experiment varies with the actual temperature of the battery as a function f (temp ); d, a value of the function f (temp) by the formula
    Figure CN105539423AC00031
    '进行归一化处理,得到作为人工神经网络的第二个输入值X2(temp),并使X2(temp)的值介于区间[0,1]。 'Is normalized, to obtain a second input value X2 (temp) as an artificial neural network, and the value of X2 (temp) is between the interval [0,1].
  7. 7. 根据权利要求5所述的结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,所述步骤3-2)中的W1 = 0.5,W2 = 0.5。 The hybrid method combines the torque distribution control Ambient temperature battery according to claim 5, wherein, in the step 3-2) W1 = 0.5, W2 = 0.5.
  8. 8. 根据权利要求1所述的结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,步骤4)中建立的目标函数式为: The hybrid method combines the torque distribution control the ambient temperature of the battery protection claimed in claim 1, wherein in step 4) established objective function is:
    Figure CN105539423AC00032
    建立的约束式为: Constraints established formula:
    Figure CN105539423AC00033
    其中,J(t)是表示整车等效燃油消耗量的目标函数,而g (r):表示瞬时等效燃油消耗量, mice(T)是发动机所消耗的燃料,me"(T)和mgene(T)分别是电动机和发电机的等效燃油消耗,T 和ω分别代表转矩和转速,i表示发动机,电动机和发电机中的一种。2Γ"(巧)表示最小转矩,7Γ'(巧)表示最大转矩,wf'表示最小转速,却胃表示最大转速。 Wherein, J (t) is a function of the equivalent target vehicle fuel consumption, and g (r): equivalent represents the instantaneous fuel consumption, mice (T) is the fuel consumed by the engine, me "(T) and mgene (T) are equivalent fuel consumption of motors and generators, T and ω represent torque and speed, i denotes an engine, a generator and a motor .2Γ "(coincidence) indicates the minimum torque, 7Γ '(Qiao) represents the maximum torque, WF' denotes a minimum speed, but indicates a maximum rotational speed of the stomach. SoC为电池剩余电量, SoCmin表示最小电池剩余容量,SoCmax表示最大电池剩余容量,Pbatt(t)电池t时刻的功率, 巧:Γ表示电池最小功率,巧Γ表示电池最大功率。 SoC is battery residual quantity, SOCmin represents the minimum residual capacity of the battery, the battery residual capacity indicates a maximum SOCmax, Pbatt (t) at time t of the battery power, Qiao: Γ represents the minimum battery power, Qiao Gamma] indicates the maximum power of the battery.
  9. 9. 根据权利要求8所述的结合环境溫度保护电池的混合动力车转矩分配控制方法,其特征在于,所述步骤4)还包括建立电动机等效燃油消耗函数式: 9. The hybrid method combines torque distribution control Ambient temperature battery according to claim 8, wherein said step 4) further comprises establishing a motor function equivalent fuel consumption formula:
    Figure CN105539423AC00034
    其中 among them
    Figure CN105539423AC00035
    I因数丫取值依赖于电动机工作状态,nch和ridch分别为电动机充、 放电过程中电动机的能量转化效率,Tm和ω。 Ah I factor value depends on the state of operation of the motor, the motor of the Nch and charge ridch respectively, the energy conversion efficiency of the motor during discharge, Tm, and ω. 分别是电动机的转矩和转速,f是优化控制参数,获得,Qlhv代表低热值; 还包括建立发动机转矩函数式:Treq = Tm+Tice,其中Treq是通过加速踏板信号得到的当前需求转矩。 Respectively, and the rotational speed of the motor torque, f is the optimal control parameters, is obtained, Qlhv representative of low calorific value; further comprising establishing an engine torque function formula: Treq = Tm + Tice, wherein the accelerator pedal signal Treq obtained by the current torque demand .
  10. 10. 结合环境溫度保护电池的混合动力车转矩分配控制系统,其特征在于,包括溫度信息采集模块、电池参数计算模块、控制处理模块W及传动系及动力学模块;所述溫度信息采集模块连接电池参数计算模块,所述电池参数计算模块连接控制处理模块,所述控制处理模块与所述传动系及动力学模块之间互连; 所述溫度信息采集模块用于采集车辆所处环境的溫度、并将环境的溫度值送给所述电池参数计算模块,所述溫度信息采集模块通过天气软件实现; 所述电池参数计算模块包括电池实际溫度计算模型和电池余量估算模型,所述电池实际溫度计算模型用于得到电池实际溫度,电池余量估算模型用于得到电池余量值,所述电池参数计算模块将得到的电池实际溫度和电池余量值送给所述控制处理模块; 所述控制处理模块包括优化控制参数处理模块和转矩分 10. A torque distribution control system of a hybrid vehicle in conjunction with a battery protection ambient temperature, characterized by comprising temperature information acquisition module, a battery parameter calculation module control processing module and W, and a drive train dynamics module; the temperature information acquisition module parameter calculation module connected to the battery, the battery control parameter calculation module connected to the processing module, the processing module and the control interconnection between the drive train and kinetics module; the temperature information collection module for collecting the environment in which the vehicle temperature, and the ambient temperature of the battery to the parameter calculation module, the temperature information acquisition module implemented by software weather; the battery module includes a battery parameter calculating temperature calculation model and the actual battery remaining amount estimation model, the battery the actual temperature calculation model for obtaining the actual temperature of the battery, the battery remaining estimation models for obtaining a battery remaining amount value, the actual battery temperature and the battery remaining amount value of said battery parameter calculation module to said obtained control processing module; the said control module comprises a processing module and a process control parameters to optimize torque points 控制优化模型模块;所述优化控制参数处理模块采用人工神经网络控制结构,用于对所述电池实际溫度和电池余量值进行处理得到优化控制参数f,所述转矩分配控制优化模型模块的作用是利用f的值结合建立的等效油耗目标函数得到发动机转矩和电动机转矩值,所述控制处理模块将得到发动机转矩和电动机转矩值送给所述传动系及动力学模块; 所述传动系及动力学模块根据发动机转矩和电动机转矩值进行转矩分配W及驱动车辆。 Optimization model control module; the optimal control parameters artificial neural network processing module is a control structure for the actual temperature of the battery and the battery remaining amount value obtained by processing the optimal control parameters F, the torque distribution control model optimization module role is to use the value of f binding target function to establish the equivalent fuel consumption obtained engine torque and the motor torque value, said control processing module obtained values ​​of the engine torque and the motor torque to said drive train and kinetics module; the kinetics of the drive train and W, and a torque distribution module according to an engine driving the vehicle and motor torque value.
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