scholarly journals Parameter Estimation of Drag Coefficient and Rolling Resistance of Vehicles Based on GPS Speed Data

2020 ◽  
Vol 5 (2) ◽  
pp. 109-115
Author(s):  
András Szántó ◽  
Sándor Hajdu
Keyword(s):  
Parameter Estimation ◽  
Drag Coefficient ◽  
Estimation Method ◽  
Rolling Resistance ◽  
Good Alternative ◽  
Resistance Coefficient ◽  
Constant Force ◽  
Force Parameter ◽  
Vehicle Model ◽  
Measurement Devices

In this paper, a parameter estimation method of the model-based design approach is applied to estimate the drag coefficient and the rolling resistance coefficient of a vehicle. In fact, a constant-force parameter (c_const) and a velocity-square-force parameter (c_square) are in the vehicle model, and these result in the sum force applied along the translational DOF that models the vehicle. It is only an assumption that the constant force is the rolling resistance and the force proportional to the square of the velocity is the drag force of the air. Only GPS speed data is used for the estimation process. The conclusion is that parameter estimation is a good alternative when expensive measurement devices are not available to measure the force losses separately and directly.

A New Computational Model about Vehicle’s Sliding Resistance Coefficients

2011 ◽  
Vol 228-229 ◽  
pp. 60-65
Author(s):  
Hong Liang Lin ◽  
Qiang Yu ◽  
Xue Li Zhang
Keyword(s):  
Drag Coefficient ◽  
Dynamic Performance ◽  
Great Influence ◽  
Rolling Resistance ◽  
Resistance Coefficient ◽  
Calculation Model ◽  
Air Drag ◽  
Sliding Resistance ◽  
Rolling Resistance Coefficient ◽  
Resistance Coefficients

Vehicle’s sliding resistance mainly includes rolling resistance, air drag resistance and friction within the transmission, wheel bearings and other related components. Among those, rolling resistance and air drag always exist whenever vehicle is running, so they have great influence on vehicle’s dynamic performance and fuel economy. Therefore, it is important to determine vehicle’s rolling resistance coefficient and air drag coefficient quickly and accurately in order to operate vehicle properly and reduce the vehicle’s fuel consumption. Combining theoretical analysis with experimental verification, calculation model based on road coasting test was given by means of least squares principle. And through which vehicle rolling resistance coefficient and air drag coefficient were determined easily. Then by using the test data from some Minibus, the vehicle's rolling resistance coefficient and air drag coefficient are calculated according to established model. The computation result shows that rolling resistance coefficient is a linear function of the speed and the air drag coefficient is constant. Finally, the analysis shows that the calculation model is simple, precise and useful.

scholarly journals In Use Determination of Aerodynamic and Rolling Resistances of Heavy-Duty Vehicles

2021 ◽  
Vol 13 (2) ◽  
pp. 974
Author(s):  
Dimitrios Komnos ◽  
Stijn Broekaert ◽  
Theodoros Grigoratos ◽  
Leonidas Ntziachristos ◽  
Georgios Fontaras
Keyword(s):  
Drag Coefficient ◽  
Fuel Consumption ◽  
Carbon Dioxide Emissions ◽  
Rolling Resistance ◽  
Resistance Coefficient ◽  
Heavy Duty ◽  
Air Drag ◽  
Speed Test ◽  
Rolling Resistance Coefficient ◽  
Heavy Duty Vehicles

A vehicle’s air drag coefficient (Cd) and rolling resistance coefficient (RRC) have a significant impact on its fuel consumption. Consequently, these properties are required as input for the certification of the vehicle’s fuel consumption and Carbon Dioxide emissions, regardless of whether the certification is done via simulation or chassis dyno testing. They can be determined through dedicated measurements, such as a drum test for the tire’s rolling resistance coefficient and constant speed test (EU) or coast down test (US) for the body’s air Cd. In this paper, a methodology that allows determining the vehicle’s Cd·A (the product of Cd and frontal area of the vehicle) from on-road tests is presented. The possibility to measure these properties during an on-road test, without the need for a test track, enables third parties to verify the certified vehicle properties in order to preselect vehicle for further regulatory testing. On-road tests were performed with three heavy-duty vehicles, two lorries, and a coach, over different routes. Vehicles were instrumented with wheel torque sensors, wheel speed sensors, a GPS device, and a fuel flow sensor. Cd·A of each vehicle is determined from the test data with the proposed methodology and validated against their certified value. The methodology presents satisfactory repeatability with the error ranging from −21 to 5% and averaging approximately −6.8%. A sensitivity analysis demonstrates the possibility of using the tire energy efficiency label instead of the measured RRC to determine the air drag coefficient. Finally, on-road tests were simulated in the Vehicle Energy Consumption Calculation Tool with the obtained parameters, and the average difference in fuel consumption was found to be 2%.

scholarly journals Novel Optimization-Based Parameter Estimation Method for the Bass Diffusion Model

SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110269
Author(s):  
Lang Liang
Keyword(s):  
Parameter Estimation ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Estimation Method ◽  
Reference Value ◽  
Diffusion Problem ◽  
Bass Model ◽  
Weighted Least Squares Method ◽  
Estimated Parameters ◽  
Bass Diffusion Model

The Bass model is the most popular model for forecasting the diffusion process of a new product. However, the controlling parameters in it are unknown in practice and need to be determined in advance. Currently, the estimation of the controlling parameters has been approached by various techniques. In this case, a novel optimization-based parameter estimation (OPE) method for the Bass model is proposed in the theoretical framework of system dynamics ( SD). To do this, the SD model of the Bass differential equation is first established and then the corresponding optimization mathematical model is formulated by introducing the controlling parameters as design variable and the discrepancy of the adopter function to the reference value as objective function. Using the VENSIM software, the present SD optimization model is solved, and its effectiveness and accuracy are demonstrated by two examples: one involves the exact solution and another is related to the actual user diffusion problem from Chinese Mobile. The results show that the present OPE method can produce higher predicting accuracy of the controlling parameters than the nonlinear weighted least squares method and the genetic algorithms. Moreover, the reliability interval of the estimated parameters and the goodness of fitting of the optimal results are given as well to further demonstrate the accuracy of the present OPE method.

scholarly journals MLE-Based Parameter Estimation for Four-Parameter Exponential Gamma Distribution and Asymptotic Variance of Its Quantiles

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2092
Author(s):  
Songbai Song ◽  
Yan Kang ◽  
Xiaoyan Song ◽  
Vijay P. Singh
Keyword(s):  
Parameter Estimation ◽  
Confidence Intervals ◽  
Asymptotic Variance ◽  
Information Matrix ◽  
Estimation Method ◽  
Flood Frequency Analysis ◽  
Annual Precipitation ◽  
Precipitation Data ◽  
Marquardt Algorithm ◽  
Design Values

The choice of a probability distribution function and confidence interval of estimated design values have long been of interest in flood frequency analysis. Although the four-parameter exponential gamma (FPEG) distribution has been developed for application in hydrology, its maximum likelihood estimation (MLE)-based parameter estimation method and asymptotic variance of its quantiles have not been well documented. In this study, the MLE method was used to estimate the parameters and confidence intervals of quantiles of the FPEG distribution. This method entails parameter estimation and asymptotic variances of quantile estimators. The parameter estimation consisted of a set of four equations which, after algebraic simplification, were solved using a three dimensional Levenberg-Marquardt algorithm. Based on sample information matrix and Fisher’s expected information matrix, derivatives of the design quantile with respect to the parameters were derived. The method of estimation was applied to annual precipitation data from the Weihe watershed, China and confidence intervals for quantiles were determined. Results showed that the FPEG was a good candidate to model annual precipitation data and can provide guidance for estimating design values

scholarly journals Modeling and Fault Diagnosis of Interturn Short Circuit for Five-Phase Permanent Magnet Synchronous Motor

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jian-wei Yang ◽  
Man-feng Dou ◽  
Zhi-yong Dai
Keyword(s):  
Parameter Estimation ◽  
Fault Diagnosis ◽  
Permanent Magnet ◽  
Fault Tolerant ◽  
Short Circuit ◽  
Estimation Method ◽  
Trust Region ◽  
Fault Tolerant Control ◽  
Trust Region Algorithm ◽  
Parameter Estimation Method

Taking advantage of the high reliability, multiphase permanent magnet synchronous motors (PMSMs), such as five-phase PMSM and six-phase PMSM, are widely used in fault-tolerant control applications. And one of the important fault-tolerant control problems is fault diagnosis. In most existing literatures, the fault diagnosis problem focuses on the three-phase PMSM. In this paper, compared to the most existing fault diagnosis approaches, a fault diagnosis method for Interturn short circuit (ITSC) fault of five-phase PMSM based on the trust region algorithm is presented. This paper has two contributions. (1) Analyzing the physical parameters of the motor, such as resistances and inductances, a novel mathematic model for ITSC fault of five-phase PMSM is established. (2) Introducing an object function related to the Interturn short circuit ratio, the fault parameters identification problem is reformulated as the extreme seeking problem. A trust region algorithm based parameter estimation method is proposed for tracking the actual Interturn short circuit ratio. The simulation and experimental results have validated the effectiveness of the proposed parameter estimation method.

Estimation of Failure Probability and its Applications in Reliability Data Analysis

2010 ◽  
Vol 118-120 ◽  
pp. 601-605
Author(s):  
Han Ming
Keyword(s):  
Parameter Estimation ◽  
Data Analysis ◽  
Bayesian Estimation ◽  
Failure Probability ◽  
Evaluation Method ◽  
Estimation Method ◽  
New Method ◽  
Reliability Parameter ◽  
Hierarchical Bayesian Estimation ◽  
Definition Of

Evaluation method of reliability parameter estimation needs to be improved effectively with the advance of science and technology. This paper develops a new method of parameter estimation, which is named E-Bayesian estimation method. In the case one hyper-parameter, the definition of E-Bayesian estimation of the failure probability is provided, moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation, and the property of E-Bayesian estimation of the failure probability are also provided. Finally, calculation on practical problems shows that the provided method is feasible and easy to perform.

Sign in / Sign up

Export Citation Format

Share Document