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CN110920625B - Decoupling and continuous estimation method for whole vehicle mass and road resistance of electric vehicle - Google Patents

Decoupling and continuous estimation method for whole vehicle mass and road resistance of electric vehicle Download PDF

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CN110920625B
CN110920625B CN201911180656.5A CN201911180656A CN110920625B CN 110920625 B CN110920625 B CN 110920625B CN 201911180656 A CN201911180656 A CN 201911180656A CN 110920625 B CN110920625 B CN 110920625B
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陈宏伟
耿聪
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Abstract

本发明实施例提供了一种电动汽车整车质量与道路阻力的解耦估计方法，包括：起步过程整车质量与路面阻力解耦估计，获取整车质量估计均值及道路阻力系数；基于整车质量估计均值，采用线性全维状态观测器，持续进行车辆行驶过程的道路阻力系数估计。本发明还提供了一种行驶循环工况下的整车质量与道路阻力的持续估计方法。本发明实施例适用于：动力系统驱动力、制动系统制动转矩可精确获取的电动汽车，包括纯电动、具有纯电起步能力的混合动力电动汽车等；行驶过程中不存在质量变化的电动汽车；估计的道路阻力系数是坡度阻力和滚动阻力的合力，不要求单独估计坡度阻力或滚动阻力。

Figure 201911180656

The embodiment of the present invention provides a method for decoupling estimation of vehicle mass and road resistance of an electric vehicle, including: decoupling estimation of vehicle mass and road resistance during starting, obtaining an estimated mean value of vehicle mass and road resistance coefficient; The mean value of mass estimation, using a linear full-dimensional state observer, continuously estimates the road resistance coefficient during the driving process of the vehicle. The present invention also provides a continuous estimation method for vehicle mass and road resistance under driving cycle conditions. The embodiments of the present invention are applicable to: electric vehicles whose driving force of the power system and braking torque of the braking system can be accurately obtained, including pure electric vehicles, hybrid electric vehicles with pure electric starting ability, etc.; Electric vehicles; estimated road drag coefficient is the combined force of grade resistance and rolling resistance, and does not require separate estimates of grade resistance or rolling resistance.

Figure 201911180656

Description

Decoupling and continuous estimation method for whole vehicle mass and road resistance of electric vehicle
Technical Field
The invention relates to the technical field of traffic, in particular to a decoupling and continuous estimation method for the whole vehicle mass and the road resistance of an electric vehicle.
Background
For electric vehicles (pure electric vehicles or hybrid electric vehicles), energy management is an important content of vehicle control. The whole vehicle quality and the road resistance are important parameters influencing the energy management and the dynamic control of the electric vehicle. Only by accurately acquiring the mass of the whole vehicle and the road surface resistance parameters, the instantaneous energy consumption of the whole vehicle can be accurately calculated, which is one of the basic conditions for energy management optimization control.
Because the mass of the whole vehicle and the road resistance cannot be directly measured, various methods and algorithms are used for parameter estimation, and the method is a main means adopted in the industry at present. For example, a method of estimating mass and gradient simultaneously using a least square method; or the quality and the gradient are simultaneously observed by adopting the self-adaptive observer, the self-adaptive law is designed by applying the Lyapunov method, the observation stability is ensured, and the observation effect is better when the gradient of the road surface has severe fluctuation behaviors such as step change and the like; or a method in which the mass and the gradient are jointly estimated using a Kalman filter.
The method for estimating the whole vehicle mass and the road resistance is carried out on the basis of coupled dynamic analysis of the whole vehicle mass and the road resistance. In the longitudinal dynamics equation of the whole vehicle, the parameter estimation of the longitudinal dynamics equation and the parameter estimation of the longitudinal dynamics equation are mutually influenced by the coupling problem, and the difficulty and the calculated amount of an algorithm are increased.
Disclosure of Invention
The embodiment of the invention provides a decoupling and continuous estimation method for the whole vehicle mass and the road resistance of an electric vehicle, which overcomes the defects of the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme.
A decoupling estimation method for the whole vehicle mass and the road resistance of an electric vehicle comprises the following steps: decoupling and estimating the whole vehicle mass and the road resistance in the starting process, and acquiring a whole vehicle mass estimation mean value and a road resistance coefficient;
and continuously estimating the road resistance coefficient in the vehicle running process by adopting a linear full-dimensional state observer based on the whole vehicle mass estimation mean value.
Preferably, the decoupling estimation of the whole vehicle mass and the road resistance in the starting process is carried out to obtain the whole vehicle mass estimation mean value and the road resistance coefficient, and the method specifically comprises the following steps:
defining the road resistance coefficient as:
μ＝sinθ+fcosθ (1)
wherein f is a road surface rolling resistance coefficient, theta is a road surface slope angle, and the formula (1) shows that the road resistance coefficient is determined by the rolling resistance coefficient and the slope angle, and the road resistance is the sum of the rolling resistance and the slope resistance;
defining the driving torque coefficient as:
Figure GDA0002932045600000021
wherein igTo the speed ratio of the gearbox, i0The speed ratio of the main speed reducer, eta transmission efficiency and r are the rolling radius of the wheel;
when an automobile starts an electric control unit to initialize, setting the initial value of the mass of the whole automobile as follows:
Figure GDA0002932045600000022
wherein m is0For preparing the mass, mtSetting the initial value of the vehicle mass as the average value of the full-load mass and the full-load mass for the full-load mass, connecting the longitudinal kinetic equations of the vehicle at two sampling moments by assuming that the road resistance coefficients at the k-1 moment and the k moment of two adjacent sampling moments are not changed, and obtaining the vehicle mass at the k moment by adopting a null method
Figure GDA0002932045600000023
The estimated values of (c) are:
Figure GDA0002932045600000031
wherein M (k) is a motor drive torque at time k,
Figure GDA0002932045600000032
the longitudinal acceleration of the whole vehicle at the moment k, a is a driving torque coefficient and is defined by a formula (2), and delta is a rotating mass equivalent coefficient;
mean value of quality estimation of n sampling points
Figure GDA0002932045600000033
And normalized variance σmComprises the following steps:
Figure GDA0002932045600000034
Figure GDA0002932045600000035
angelicae sinensis for normalizing variance σmIs less than a set threshold value sigmam0When the mass estimation value is stable, the estimation is stopped, and the mean value of the mass estimation value of the whole vehicle at the moment is used
Figure GDA0002932045600000036
As a final result of the estimated quality, corresponding to the estimated quality
Figure GDA0002932045600000037
The road resistance coefficient of (a) is:
Figure GDA0002932045600000038
wherein n is the sampling frequency when stopping mass estimation, and g is the gravity acceleration.
Preferably, the continuously estimating the road resistance coefficient in the vehicle running process by using a linear full-dimensional state observer based on the vehicle mass estimation mean value comprises:
taking the finished automobile mass estimation value obtained in the formula (5) as an optimal value of finished automobile mass estimation, and keeping the finished automobile mass as a constant in the driving process;
defining equivalent driving/braking force Feq：
Figure GDA0002932045600000039
Wherein, M is the driving torque of the driving motor or the power assembly, M is a positive value during driving, and M is a negative value during braking if a feedback braking function exists; v is vehicle speed, ρ is air density, CdIs the wind resistance coefficient, AvIs the frontal area, Tb(i) The braking torque of each wheel brake, r is the rolling radius of the wheel;
setting a system state vector X as a two-dimensional column vector consisting of a longitudinal speed v and a road resistance coefficient mu, and setting an input quantity U as an equivalent driving/braking force FeqAnd a two-dimensional column vector formed by 0, wherein the system output Y is a longitudinal speed v:
Figure GDA0002932045600000041
the system state space model is as follows:
Figure GDA0002932045600000042
in equation (10), the matrices A, B, C are:
Figure GDA0002932045600000043
the system observation feedback matrix is set as follows:
Figure GDA0002932045600000044
λ in formula (12)1、λ2Are closed-loop system characteristic values, which are negative real numbers;
a linear full-dimensional state observer is designed by utilizing the system input quantity U, the output quantity Y and the observation feedback matrix G to realize the estimation of a system state vector X, and the closed-loop system state equation of the linear full-dimensional state observer can be expressed as follows:
Figure GDA0002932045600000045
discretizing the matrix differential equation (13) into a differential equation and solving the differential equation to obtain a real-time estimation of a system state vector X, namely a road resistance coefficient mu, and after the system constant matrix A, B, C, G is determined, carrying out the road resistance coefficient estimation according to the equation (13) in real time and continuously in the driving process after the vehicle starts so as to estimate the road resistance condition which is possibly and continuously changed;
when the road surface rolling resistance coefficient f is known, according to the estimated value of the road resistance coefficient mu, the road slope angle is obtained as follows:
Figure GDA0002932045600000051
a continuous estimation method for the whole vehicle mass and the road resistance under the running cycle working condition comprises the following specific steps:
1) VCU initialization: when the starting switch is turned ON to the ON position, the VCU sequentially realizes electrification, self-inspection and initialization, and assigns values to parameter variables required by the estimation of the whole vehicle mass and the road resistance;
2) estimating the vehicle mass for the first time of vehicle starting: the initial value of the automobile mass is the average value of the entire mass and the full load mass, the first mass estimation is carried out according to the formulas (1) to (7), and the average value of the mass estimation values is used as the optimal value of the whole automobile mass estimation after convergence;
3) different road resistance estimations are performed depending on the vehicle acceleration: after the estimation of the mass of the whole vehicle is converged for the first time, the mass of the whole vehicle is considered as a constant;
when the acceleration is larger than or equal to zero, the whole vehicle is in the acceleration or uniform speed driving stage, and F is calculated according to the equivalent driving force formula of the formula (8)eqSolving a differential equation (13) to estimate the road resistance in the driving process;
when the acceleration is less than zero, the whole vehicle is in the deceleration braking driving stage, and F is calculated according to the formula (8) of the equivalent braking forceeqSolving a differential equation (13) to estimate the road resistance in the braking process;
when the vehicle speed is not zero, continuously estimating the road resistance in the driving and braking processes through the positive and negative of the acceleration;
4) judging and deciding the parking state: when the vehicle speed is zero, the vehicle stops, and the driving intention of a driver is judged through a starting switch at the moment;
if the starting switch is in the OFF position, the driving intention is to stop the vehicle for a long time, and the program operation is ended;
if the starting switch is still in the ON position, the temporary stop is indicated, and the driver is waited to start again;
5) estimating the mass of the whole vehicle after temporary parking again: when the vehicle is started again after being stopped, the vehicle gets on/off passengers or loads and unloads goods, the mass of the whole vehicle is changed, and the mass estimation is carried out again; and at the moment, the finished automobile mass estimation convergence value before parking is used as an initial value of the next round of mass estimation, and the mass estimation module is returned to perform mass estimation again.
According to the technical scheme provided by the embodiment of the invention, the embodiment of the invention provides a decoupling and continuous estimation method for the whole vehicle mass and the road resistance of the electric vehicle, which is applicable to the following ranges:
(1) the electric automobile with accurately obtained driving force of a power system and braking torque of a braking system comprises a pure electric automobile, a hybrid electric automobile with pure electric starting capability and the like.
(2) The electric automobile has no mass change in the driving process.
(3) The estimated road resistance coefficient is the resultant of the grade and rolling resistances, and does not require a separate estimation of either grade or rolling resistance.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic diagram of a decoupling estimation process of the whole vehicle mass and the road surface resistance in a starting process;
FIG. 2 is a schematic diagram of a continuous estimation process of vehicle mass and road resistance under a driving cycle condition.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
For the convenience of understanding the embodiments of the present invention, the following description will be further explained by taking several specific embodiments as examples in conjunction with the drawings, and the embodiments are not to be construed as limiting the embodiments of the present invention.
The embodiment of the invention provides a decoupling estimation method for the whole vehicle mass and the road resistance of an electric vehicle, which specifically comprises the following steps:
1. decoupling estimation is carried out on the whole vehicle mass and the road resistance in the starting process, and a whole vehicle mass estimation mean value and a road resistance coefficient are obtained, as shown in fig. 1, the method comprises the following steps:
the electric automobile and the hybrid electric automobile are both started electrically, the motor driving torque can be accurately obtained, and the mass of the whole automobile can be considered as a constant in the driving process. In consideration of the characteristics, based on the analysis of the longitudinal dynamics of the automobile, the following decoupling estimation algorithm is provided.
Defining the road resistance coefficient as:
μ＝sinθ+fcosθ (1)
wherein f is the road surface rolling resistance coefficient, and theta is the road surface slope angle. From the equation (1), the road resistance coefficient is determined by the rolling resistance coefficient and the slope angle. Road resistance, as defined herein, is the sum of rolling resistance and grade resistance.
Defining the driving torque coefficient as:
Figure GDA0002932045600000081
wherein igTo the speed ratio of the gearbox, i0The speed ratio of the main speed reducer, eta transmission efficiency and r are the rolling radius of the wheel.
When an automobile starts an electric control unit to initialize, setting the initial value of the mass of the whole automobile as follows:
Figure GDA0002932045600000082
wherein m is0For preparing mass mtIs the full load mass. Namely, the initial value of the mass of the whole vehicle is set as the average value of the service mass and the full load mass. Assuming that the road resistance coefficients of two adjacent sampling moments (k-1 moment and k moment) are not changed, connecting the automobile longitudinal dynamics equations of the two sampling moments, and obtaining the automobile mass at the k moment by adopting an elimination method
Figure GDA0002932045600000083
The estimated values of (c) are:
Figure GDA0002932045600000084
where M (k) is the motor drive torque at time k,
Figure GDA0002932045600000091
the longitudinal acceleration of the whole vehicle at the moment k, a is a driving torque coefficient and is defined by an equation (2), and delta is a rotating mass equivalent coefficient.
Mean value of quality estimation of n sampling points
Figure GDA0002932045600000092
And normalized variance σmComprises the following steps:
Figure GDA0002932045600000093
Figure GDA0002932045600000094
angelicae sinensis for normalizing variance σmIs less than a set threshold value sigmam0Considering the mass estimation value to be stable, stopping estimation, and taking the mean value of the mass estimation value of the whole vehicle at the moment
Figure GDA0002932045600000095
As a final result of estimating the quality. Corresponding to the estimated quality
Figure GDA0002932045600000096
The road resistance coefficient of (a) is:
Figure GDA0002932045600000097
where n is the sampling time when stopping the quality estimation.
The method for estimating the decoupling of the vehicle mass and the road resistance, which is composed of the formulas (1) to (7), is shown in a program block diagram of fig. 1.
2. And (3) continuously estimating the road resistance coefficient in the vehicle running process by adopting a linear full-dimensional state observer based on the whole vehicle mass estimation mean value:
after the estimated value of the whole vehicle mass given by the formula (5) is obtained, the best estimation result of the whole vehicle mass is considered, and the whole vehicle mass is kept constant in the driving process. On the basis, a linear full-dimensional state observer for estimating the road resistance coefficient is provided, and the road resistance coefficient estimation of the vehicle in the running process is continuously carried out.
Defining equivalent driving/braking force Feq：
Figure GDA0002932045600000101
Wherein, M is the driving torque of the driving motor or the power assembly, and M is a positive value during driving, and if a feedback braking function exists, M is a negative value during braking. v is vehicle speed, ρ is air density, CdIs the wind resistance coefficient, AvIs the frontal area, Tb(i) R is the wheel rolling radius, which is the braking torque of each wheel brake.
Setting a system state vector X as a two-dimensional column vector consisting of a longitudinal speed v and a road resistance coefficient mu, and setting an input quantity U as an equivalent driving/braking force FeqAnd a two-dimensional column vector formed by 0, wherein the system output Y is a longitudinal speed v:
Figure GDA0002932045600000102
the system state space model is as follows:
Figure GDA0002932045600000103
Y＝CX (10)
in equation (10), the matrices A, B, C are:
Figure GDA0002932045600000104
the system observation feedback matrix is set as follows:
Figure GDA0002932045600000105
λ in formula (12)1、λ2The characteristic values of the closed-loop system are negative real numbers.
And designing a linear full-dimensional state observer by using the system input quantity U, the output quantity Y and the observation feedback matrix G to realize the estimation of the system state vector X. The linear full-dimensional state observer closed-loop system state equation can be expressed as:
Figure GDA0002932045600000111
and discretizing the matrix differential equation (13) into a differential equation and solving the differential equation to obtain the real-time estimation of a system state vector X, namely the road resistance coefficient mu. After the system constant matrix A, B, C, G is determined, road resistance coefficient estimation as per equation (13) is continued in real time during vehicle travel after vehicle launch to estimate road resistance conditions that may be constantly changing.
When the road surface rolling resistance coefficient f is known, according to the estimated value of the road resistance coefficient mu, the road slope angle is obtained as follows:
Figure GDA0002932045600000112
(8) a method for estimating a road drag coefficient by a linear full-dimensional state observer, which comprises the following expressions (14).
The invention also provides a continuous estimation method of the whole vehicle mass and the road resistance under the running cycle working condition, as shown in fig. 2, the specific steps are as follows:
in various driving cycles, the vehicle sequentially drives in the states of starting, accelerating, uniform speed, decelerating and braking, temporary stopping and the like. Different estimation strategies of the whole vehicle mass and the road resistance are put forward in a targeted manner at different stages of the driving cycle, and real-time continuous estimation of the two parameters is realized.
1) VCU initialization
When the starting switch is turned ON to the ON position, the VCU sequentially realizes electrification, self-checking and initialization, and assigns values to parameter variables required by the whole vehicle mass and the road resistance estimation.
2) First vehicle mass estimation for vehicle launch
And the initial value of the automobile mass is the average value of the entire mass and the full-load mass, the first mass estimation is carried out according to the formulas (1) to (7), and the average value of the mass estimation value is taken as the optimal value of the whole automobile mass estimation after convergence.
3) Implementing different road resistance estimations according to vehicle acceleration
After the first vehicle mass estimation converges, the mass is considered to be a constant.
When the acceleration is larger than or equal to zero, the whole vehicle is in the acceleration or constant speed driving stage, and F is calculated by the road resistance module in the constant speed/acceleration process according to the formula (8) equivalent driving force formulaeqAnd solving a differential equation (13) to estimate the road resistance in the driving process.
When the acceleration is less than zero, the whole vehicle is in the deceleration braking driving stage, and F is calculated by the road resistance module in the braking process according to the formula (8) equivalent braking force formulaeqAnd solving a differential equation (13) to estimate the road resistance in the braking process.
When the vehicle speed is not zero, the road resistance estimation in the driving and braking process is continuously carried out through the positive and negative of the acceleration.
4) Determination and decision of parking status
When the vehicle speed is zero, the vehicle is stopped, and the driving intention of the driver is judged through the starting switch.
If the start switch is in the OFF position, indicating that the driving intention is a long-time stop, the program operation is ended.
If the start switch is still in the ON position, indicating a temporary stop, the driver is waited to take off again.
5) Re-estimation of vehicle mass after temporary stop
When the vehicle is started again after being stopped, the vehicle is possible to get on/off passengers or load and unload goods, the mass of the whole vehicle is changed, and the mass estimation needs to be carried out again. And at the moment, the convergence value of the whole vehicle mass estimation before parking is used as an initial value of the next round of mass estimation, and the mass estimation is carried out again according to the formulas (1) to (7) by returning to the mass estimation calculation module.
The continuous estimation strategy of the whole vehicle mass and the road resistance under the driving cycle working condition is shown as a program block diagram shown in fig. 2.
In summary, the embodiments of the present invention provide a whole vehicle mass estimation method based on a decoupling algorithm, a road resistance estimation method using a full-dimensional state observer and considering driving and braking processes, and a control strategy for continuously estimating the whole vehicle mass and the road resistance at different stages of a driving cycle for the first time, aiming at the characteristics of an electric vehicle, and the calculation method is simple and practical, and can be used in a vehicle real-time control system requiring on-line estimation of the whole vehicle mass and the road resistance coefficient.
Those of ordinary skill in the art will understand that: the figures are merely schematic representations of one embodiment, and the blocks or flow diagrams in the figures are not necessarily required to practice the present invention.
From the above description of the embodiments, it is clear to those skilled in the art that the present invention can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for apparatus or system embodiments, since they are substantially similar to method embodiments, they are described in relative terms, as long as they are described in partial descriptions of method embodiments. The above-described embodiments of the apparatus and system are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (3)

1.一种电动汽车整车质量与道路阻力的解耦估计方法，其特征在于，包括：起步过程整车质量与路面阻力解耦估计，获取整车质量估计均值及道路阻力系数；1. a decoupling estimation method of electric vehicle vehicle mass and road resistance, is characterized in that, comprising: starting process vehicle mass and road resistance decoupling estimation, obtain vehicle mass estimated mean value and road resistance coefficient; 基于所述整车质量估计均值，采用线性全维状态观测器，持续进行车辆行驶过程的道路阻力系数估计；Based on the estimated mean value of the entire vehicle mass, a linear full-dimensional state observer is used to continuously estimate the road resistance coefficient during the driving process of the vehicle; 所述起步过程整车质量与路面阻力解耦估计，获取整车质量估计均值及道路阻力系数，具体包括以下步骤：In the starting process, the decoupling estimation of the vehicle mass and the road resistance is performed, and the estimated mean value of the vehicle mass and the road resistance coefficient are obtained, which specifically includes the following steps: 定义道路阻力系数为：The road resistance coefficient is defined as: μ＝sinθ+f cosθ (1)μ=sinθ+f cosθ (1) 其中，f为路面滚动阻力系数，θ为路面坡度角，由(1)式可知，道路阻力系数由滚动阻力系数和坡度角决定，道路阻力是滚动阻力和坡度阻力的和；Among them, f is the rolling resistance coefficient of the road surface, and θ is the slope angle of the road surface. It can be seen from the formula (1) that the road resistance coefficient is determined by the rolling resistance coefficient and the slope angle, and the road resistance is the sum of the rolling resistance and the slope resistance; 定义驱动转矩系数为：Define the drive torque coefficient as:
Figure FDA0002932045590000011
Figure FDA0002932045590000011
 其中，ig为变速箱速比，i0为主减速器速比，η传动效率，r为车轮滚动半径；Among them, i g is the speed ratio of the gearbox, i 0 is the speed ratio of the main reducer, η is the transmission efficiency, and r is the wheel rolling radius; 在汽车起动电控单元初始化时，设定整车质量初值为：During the initialization of the vehicle starting electronic control unit, the initial value of the vehicle mass is set as:
Figure FDA0002932045590000012
Figure FDA0002932045590000012
 其中，m0为整备质量，mt为满载质量，即设定整车质量初值为整备质量和满载质量的平均值，假定两个相邻采样时刻k－1时刻和k时刻的道路阻力系数不变，联列两个采样时刻的汽车纵向动力学方程，采用消元法，得到k时刻的汽车质量
Figure FDA0002932045590000013
的估计值为：Among them, m 0 is the curb mass, m t is the full load mass, that is, the initial value of the vehicle mass is set as the average value of the curb mass and the full load mass, and the road resistance coefficient at the two adjacent sampling times k-1 and k is assumed. Invariant, concatenate the vehicle longitudinal dynamics equations at two sampling times, and use the elimination method to obtain the vehicle mass at time k
Figure FDA0002932045590000013
is estimated to be:
Figure FDA0002932045590000021
Figure FDA0002932045590000021
 其中，M(k)为k时刻的电机驱动转矩，
Figure FDA0002932045590000022
为k时刻的整车纵向加速度，a为驱动转矩系数，由式(2)定义，δ为旋转质量等效系数；Among them, M(k) is the motor driving torque at time k,
Figure FDA0002932045590000022
is the longitudinal acceleration of the vehicle at time k, a is the driving torque coefficient, defined by formula (2), and δ is the equivalent coefficient of the rotating mass; n个采样点质量估计均值
Figure FDA0002932045590000023
和归一化方差σm为：mean of quality estimates for n sampling points
Figure FDA0002932045590000023
and the normalized variance σ m is:
Figure FDA0002932045590000024
Figure FDA0002932045590000024
Figure FDA0002932045590000025
Figure FDA0002932045590000025
 当归一化方差σm的值小于设定的阈值σm0时，质量估计值已经稳定，停止估计，将此时整车质量估计值的均值
Figure FDA0002932045590000026
作为估计质量的最终结果，对应该估计质量
Figure FDA0002932045590000027
的道路阻力系数为：When the value of the normalized variance σ m is less than the set threshold σ m0 , the estimated quality value has been stabilized, and the estimation is stopped, and the average value of the estimated quality value of the entire vehicle at this time is calculated.
Figure FDA0002932045590000026
As a final result of the estimated mass, the corresponding mass should be estimated
Figure FDA0002932045590000027
The road resistance coefficient is:
Figure FDA0002932045590000028
Figure FDA0002932045590000028
 其中，n为停止质量估计时的采样次数，g为重力加速度。Among them, n is the sampling times when stopping mass estimation, and g is the gravitational acceleration. 2.根据权利要求1所述的方法，其特征在于，所述基于所述整车质量估计均值，采用线性全维状态观测器，持续进行车辆行驶过程的道路阻力系数估计，包括：2. The method according to claim 1, characterized in that, based on the estimated mean value of the entire vehicle mass, a linear full-dimensional state observer is used to continuously estimate the road resistance coefficient during the driving process of the vehicle, comprising: 将(5)式得出的整车质量估计值作为整车质量估计的最佳值，在行驶过程中整车质量保持为常数；Take the estimated value of the vehicle mass obtained by formula (5) as the best value of the estimated vehicle mass, and keep the vehicle mass constant during the driving process; 定义等效驱动/制动力Feq：Define the equivalent driving/braking force F eq :
Figure FDA0002932045590000031
Figure FDA0002932045590000031
 其中，M为驱动电机或动力总成驱动转矩，驱动时M为正值，若有回馈制动功能，制动时M为负值；v为车速，ρ为空气密度、Cd为风阻系数、Av为迎风面积，Tb(i)为各车轮制动器的制动力矩，r为车轮滚动半径；Among them, M is the driving torque of the drive motor or powertrain, and M is a positive value when driving. If there is a regenerative braking function, M is a negative value when braking; v is the vehicle speed, ρ is the air density, and C d is the wind resistance coefficient , A v is the windward area, T b (i) is the braking torque of each wheel brake, r is the wheel rolling radius; 设系统状态向量X为纵向速度v、道路阻力系数μ构成的二维列向量，输入量U为等效驱动/制动力Feq与0构成的二维列向量，系统输出Y为纵向速度v：Let the system state vector X be the two-dimensional column vector composed of the longitudinal speed v and the road resistance coefficient μ, the input quantity U is the two-dimensional column vector composed of the equivalent driving/braking force F eq and 0, and the system output Y is the longitudinal speed v:
Figure FDA0002932045590000032
Figure FDA0002932045590000032
 系统状态空间模型为：The system state space model is:
Figure FDA0002932045590000033
Figure FDA0002932045590000033
 式(10)中，矩阵A、B、C分别为：In formula (10), the matrices A, B, and C are respectively:
Figure FDA0002932045590000034
Figure FDA0002932045590000034
 设系统观测反馈矩阵为：Let the system observation feedback matrix be:
Figure FDA0002932045590000035
Figure FDA0002932045590000035
 式(12)中λ1、λ2是闭环系统特征值，均为负实数；In formula (12), λ 1 and λ 2 are the eigenvalues of the closed-loop system, both of which are negative real numbers; 利用系统输入量U、输出量Y、观测反馈矩阵G，设计线性全维状态观测器，实现对系统状态向量X的估计，线性全维状态观测器闭环系统状态方程可表示为：Using the system input U, output Y, and observation feedback matrix G, a linear full-dimensional state observer is designed to estimate the system state vector X. The state equation of the closed-loop system of the linear full-dimensional state observer can be expressed as:
Figure FDA0002932045590000041
Figure FDA0002932045590000041
 将矩阵微分方程(13)离散化为差分方程并求解之，得到对系统状态向量X，即道路阻力系数μ的实时估计，在系统常数矩阵A、B、C、G确定后，按方程(13)进行的道路阻力系数估计，在车辆起步后的行驶过程中是实时连续进行的，以估计可能不断变化的道路阻力情况；The matrix differential equation (13) is discretized into a difference equation and solved to obtain a real-time estimation of the system state vector X, that is, the road resistance coefficient μ. After the system constant matrix A, B, C, and G are determined, according to equation (13) ), which is continuously performed in real time during the driving process after the vehicle starts, to estimate the possibly changing road resistance situation; 当已知路面滚动阻力系数f时，根据道路阻力系数μ的估计值，可得到道路坡度角为：When the road rolling resistance coefficient f is known, according to the estimated value of the road resistance coefficient μ, the road slope angle can be obtained as:
Figure FDA0002932045590000042
Figure FDA0002932045590000042
 3.一种行驶循环工况下的整车质量与道路阻力的持续估计方法，其特征在于，利用权利要求2所述的电动汽车整车质量与道路阻力的解耦估计方法，具体步骤包括：3. the continuous estimation method of vehicle mass and road resistance under a driving cycle operating condition, it is characterized in that, utilize the decoupling estimation method of the described electric vehicle vehicle quality of claim 2 and road resistance, concrete steps comprise: 1)VCU初始化：当启动开关打开至ON位置时，VCU依次实现上电、自检、初始化，将整车质量和道路阻力估计需要的参数变量赋值；1) VCU initialization: When the start switch is turned on to the ON position, the VCU implements power-on, self-test, and initialization in sequence, and assigns the parameter variables required for the estimation of the vehicle mass and road resistance; 2)车辆起步的首次整车质量估计：汽车质量赋初值为整备质量和满载质量的平均值，按(1)～(7)式进行首次质量估计，收敛后将质量估计值均值作为整车质量估计的最佳值；2) The first vehicle mass estimation at the start of the vehicle: the initial value of the vehicle mass is the average value of the curb weight and the full load weight, and the first mass estimation is carried out according to equations (1) to (7). the best value of the quality estimate; 3)根据车辆加速度实施不同的道路阻力估计：首次整车质量估计收敛后，认为整车质量是常数；3) Implement different road resistance estimates according to vehicle acceleration: after the first vehicle mass estimation converges, the vehicle mass is considered to be constant; 当加速度大于或等于零时，整车处于加速或匀速行驶阶段，按(8)式的等效驱动力公式计算Feq，求解微分方程(13)，进行驱动过程的道路阻力估计；When the acceleration is greater than or equal to zero, the whole vehicle is in the acceleration or constant speed driving stage, calculate F eq according to the equivalent driving force formula of formula (8), solve the differential equation (13), and estimate the road resistance in the driving process; 当加速度小于零时，整车处于减速制动行驶阶段，按(8)式的等效制动力公式计算Feq，求解微分方程(13)，进行制动过程的道路阻力估计；When the acceleration is less than zero, the whole vehicle is in the stage of deceleration braking, calculate F eq according to the equivalent braking force formula of formula (8), solve the differential equation (13), and estimate the road resistance during the braking process; 当车速不为零时，通过加速度的正负，持续进行驱动和制动过程的道路阻力估计；When the vehicle speed is not zero, the road resistance estimation of the driving and braking process is continuously performed through the positive and negative acceleration; 4)停车状态的判断和决策：当车速为零时，车辆停车，此时通过起动开关判断驾驶员驾驶意图；4) Judgment and decision-making of parking status: when the vehicle speed is zero, the vehicle stops, and the driver's driving intention is judged by the start switch at this time; 如果启动开关处于OFF位置，表明驾驶意图是长时间停车，结束程序运行；If the start switch is in the OFF position, it indicates that the driving intention is to stop for a long time and end the program operation; 如果启动开关仍然处于ON位置，表明是临时停车，等待驾驶员再次起步；If the start switch is still in the ON position, it indicates that it is a temporary stop, waiting for the driver to start again; 5)临时停车后的整车质量再次估计：当车辆停车后再次起步时，汽车上/下乘客或装卸货物，整车质量将有变化，重新进行质量估计；此时将停车前的整车质量估计收敛值，作为下一轮质量估计的初值，返回质量估计模块，重新进行质量估计。5) Re-estimate the quality of the vehicle after temporary parking: When the vehicle starts again after parking, the vehicle loads/unloads passengers or loads and unloads goods, the vehicle quality will change, and the quality of the vehicle will be re-estimated; at this time, the vehicle quality before parking will be re-estimated. The estimated convergence value is used as the initial value of the next round of quality estimation, and is returned to the quality estimation module to perform quality estimation again.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102951158A (en) * 2012-11-02 2013-03-06 浙江吉利汽车研究院有限公司杭州分公司 Vehicle mass estimation method
CN108944935A (en) * 2018-05-31 2018-12-07 重庆大学 A kind of car mass and road grade estimation method considering parameter coupled relation
CN109477754A (en) * 2016-06-30 2019-03-15 米其林集团总公司 Method and apparatus for determining motor vehicles gross mass estimated value
CN109489787A (en) * 2018-10-05 2019-03-19 鸿运汽车有限公司 A kind of vehicle vertical load and road gradient estimating system and its estimation method
CN110395266A (en) * 2019-08-14 2019-11-01 厦门金龙联合汽车工业有限公司 A kind of evaluation method decoupled about bus mass change and road grade

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102951158A (en) * 2012-11-02 2013-03-06 浙江吉利汽车研究院有限公司杭州分公司 Vehicle mass estimation method
CN109477754A (en) * 2016-06-30 2019-03-15 米其林集团总公司 Method and apparatus for determining motor vehicles gross mass estimated value
CN108944935A (en) * 2018-05-31 2018-12-07 重庆大学 A kind of car mass and road grade estimation method considering parameter coupled relation
CN109489787A (en) * 2018-10-05 2019-03-19 鸿运汽车有限公司 A kind of vehicle vertical load and road gradient estimating system and its estimation method
CN110395266A (en) * 2019-08-14 2019-11-01 厦门金龙联合汽车工业有限公司 A kind of evaluation method decoupled about bus mass change and road grade

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