Dynamik der Kraftfahrzeuge

Mitschke, Manfred; Wallentowitz, Henning

doi:10.1007/978-3-658-05068-9

Cited by 181 publications

(112 citation statements)

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“…According to the driving behavioral characteristics of operating vehicles, the acceleration of operating vehicle in typical driving condition generally does not exceed 2.5 m/s 2 [12]. On the other hand, deceleration of most operating vehicles on dry pavement does not exceed 3.5 m/s 2 [13]. Therefore, speed change rate of -3.5~2.5 m/s 2 is set as the threshold value.…”

Section: Data Cleaning For Outlying Accelerationmentioning

confidence: 99%

Data Cleaning of Speed Monitoring Based on Driving Behavior Characteristics for Commercial Vehicle

Sun

Wang

Xie

et al. 2018

IOP Conf. Ser.: Mater. Sci. Eng.

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There are lots of speed monitoring data in the commercial vehicle monitoring system, and the accuracy of the data depends on accuracy of the analysis for driving behavior characteristics. In this paper, the driving behavior characteristics for commercial vehicles is analyzed so that six common types of errors for vehicle monitoring data are obtained, such as false date for time information, outlying high/low speed values, zero-speed signal drift, false zero-speed records, outlying acceleration/deceleration values, noise jamming data. Then data cleaning rules are made. Finally, we compare data cleaning effect through typical data source case. Results show that the data cleaning method is used for fitting the data, and correct the error signal from the vehicle driving curves more correspond with the real-world driving and road conditions.

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Section: Data Cleaning For Outlying Accelerationmentioning

confidence: 99%

Data Cleaning of Speed Monitoring Based on Driving Behavior Characteristics for Commercial Vehicle

Sun

Wang

Xie

et al. 2018

IOP Conf. Ser.: Mater. Sci. Eng.

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“…Research in these areas of automotive engineering has been carried out by many authors in recent years. Some of the most comprehensive books and monographs are [1][2][3][4], and the main results and models described by their authors have been taken into account and used in this research work. Shock absorbers heat load and oil temperature are studied in the literature [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Influence of shock absorber temperature on vehicle ride comfort and road holding

Павлов

2017

MATEC Web Conf.

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“…This factor also depends on the speed of travel and increases with its growth; this is related to the increase in tire deformation. The value of the rolling resistance coefficient is usually given by the tire manufacturer, and exemplary values and empirical models on the dependence of this coefficient on the speed function can be found in the literature [16]. For low travel speeds (<40km/h), the value of the rolling resistance coefficient is assumed to be constant, independent of speed.…”

Section: Mathematical Model Of the Vehiclementioning

confidence: 99%

“…The bearing torque is proportional to the bearing load, friction coefficient, and bearing radius. Bearing friction is generally neglected, as the bearing resistance value is small compared to the tire rolling resistance [16].…”

Section: Mathematical Model Of the Vehiclementioning

confidence: 99%

Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars

Targosz

Skarka

Przystałka

2018

Journal of Advanced Transportation

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The article presents a method for optimizing driving strategies aimed at minimizing energy consumption while driving. The method was developed for the needs of an electric powered racing vehicle built for the purposes of the Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. Model-based optimization was used to determine the driving strategy. The numerical model was elaborated in Simulink environment, which includes both the electric vehicle model and the environment, i.e., the race track as well as the vehicle environment and the atmospheric conditions. The vehicle model itself includes vehicle dynamic model, numerical model describing issues concerning resistance of rolling tire, resistance of the propulsion system, aerodynamic phenomena, model of the electric motor, and control system. For the purpose of identifying design and functional features of individual subassemblies and components, numerical and stand tests were carried out. The model itself was tested on the research tracks to tune the model and determine the calculation parameters. The evolutionary algorithms, which are available in the MATLAB Global Optimization Toolbox, were used for optimization. In the race conditions, the model was verified during SEM races in Rotterdam where the race vehicle scored the result consistent with the results of simulation calculations. In the following years, the experience gathered by the team gave us the vice Championship in the SEM 2016 in London.

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Dynamik der Kraftfahrzeuge

Cited by 181 publications

References 0 publications

Data Cleaning of Speed Monitoring Based on Driving Behavior Characteristics for Commercial Vehicle

Data Cleaning of Speed Monitoring Based on Driving Behavior Characteristics for Commercial Vehicle

Influence of shock absorber temperature on vehicle ride comfort and road holding

Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars

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