Simulation of Driveability in Real-time

Zehetner, Josef; Schöggl, Peter; Dank, Matthias; Meitz, Klaus

doi:10.4271/2009-01-1372

Cited by 22 publications

(4 citation statements)

References 1 publication

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“…13b). The (18) ΔOR Vn,x,y = OR Vn,x,y − OR V1,x,y clearest differences can be observed for V4 in Fig. 13c.…”

Section: Overall Ratings and Difference Plotsmentioning

confidence: 88%

“…In order to reduce costs and test duration, it is helpful to reduce the number of measurements performed on a test track or in real traffic situations. Roadto-rig solutions [17] or simulations [18] appear to be very promising. When using these methods, calibration engineers cannot rely on their experience to evaluate the driveability since important physical information is not perceptible (e.g., longitudinal, lateral and vertical acceleration).…”

Section: Introductionmentioning

confidence: 99%

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Objective Rating of the Launch Behavior of Conventional, Hybrid and Electric Vehicles

2021

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The calibration of conventional, hybrid and electric drivetrains is an important process during the development phase of any vehicle. Therefore, to optimize the comfort and dynamic behavior (known as driveability), many test drives are performed by experienced drivers during different driving maneuvers, e.g., launch, re-launch or gear shift. However, the process can be kept more consistent and independent of human-based deviations by using objective ratings. This study first introduces an objective rating system developed for the launch behavior of conventional vehicles with automatic transmission, dual-clutch transmission, and alternative drivetrains. Then, the launch behavior, namely comfort and dynamic quality, is compared between two conventional vehicles, a plug-in hybrid electric vehicle and a battery electric vehicle. Results show the benefits of pure electric drivetrains due to the lack of launch and shifting elements, as well as the usage of a highly dynamic electric motor. While the plug-in hybrid achieves a 10% higher overall rating compared to the baseline conventional vehicle, the pure electric vehicle even achieves a 21% higher overall rating. The results also highlight the optimization potential of battery electric vehicles regarding their comfort and dynamic characteristics. The transitions and the gradient of the acceleration build-up have a major influence on the launch quality.

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“…13b). The (18) ΔOR Vn,x,y = OR Vn,x,y − OR V1,x,y clearest differences can be observed for V4 in Fig. 13c.…”

Section: Overall Ratings and Difference Plotsmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Objective Rating of the Launch Behavior of Conventional, Hybrid and Electric Vehicles

2021

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“…Hayat et al established various subsystem models that affect driveability [6]. Zehetner et al proposed a new method for the economy, emission and driveability [7]. A method that can quantitatively evaluate the driveability of heavy vehicles was proposed [8].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Subjective Evaluation Method of Driveability for Fuel Cell Vehicles

Zhan,

Zhu,

Duan

et al. 2024

Energies

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Aiming at the demand for subjective evaluation of driveability for fuel cell vehicles, the modeling and evaluation method of driveability for fuel cell vehicles were studied in this paper. Firstly, a real-time model of the fuel cell vehicle powertrain system was established, which included the fuel cell model, power battery model, DC/DC converter model and drive motor model. Secondly, it was integrated with the vehicle dynamics model to form a virtual prototype of a fuel cell vehicle. And a virtual subjective evaluation platform for fuel cell vehicles was built by combining the virtual prototype and high-fidelity driving simulator. Thirdly, a subjective evaluation method of driveability for fuel cell vehicles was proposed, which included the starting performance, acceleration performance, uniform speed performance and tip-in/tip-out performance. Finally, the paper used the platform and method mentioned above to conduct subjective evaluations of the fuel cell vehicles.

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“…These objective evaluation methods for vehicle dynamic performance can be further divided into two categories. The first category includes evaluating the performance of a vehicle through a bench test, a simulation test, or a driving simulation experiment [7,8] or presenting evaluation methods of dynamic performance based on simulation platforms [9]. The second category evaluates the dynamic performance through road tests; for instance, Wei proposed an objective evaluation system with evaluation indices related to dynamic performance and drivability as well as the test conditions of all indices [10].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Relationships between Subjective Evaluations and Objective Metrics of Vehicle Dynamic Performance

Zhao

Liu

Yang

et al. 2018

Journal of Advanced Transportation

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This study explored the relationships between subjective evaluations and objective metrics of vehicle dynamic performance. First, a real vehicle test was performed to measure the acceleration performance under different conditions, and participants’ subjective evaluations of the acceleration performance were investigated. Second, correlation analysis was conducted to explore relationships between each subjective evaluation and its corresponding objective metric as well as between the overall subjective evaluation and three individual subjective evaluations. Finally, an overall subjective evaluation model related to the three objective metrics was established based on the Probabilistic Neural Network (PNN). The analysis results demonstrated that the correlation coefficients of the three groups of data were greater than 0.5 and that each subjective evaluation was significantly correlated with its corresponding objective metric. The individual subjective evaluation of the climbing acceleration performance had the largest effect on the overall subjective evaluation, with a correlation coefficient of 0.47. The established overall subjective evaluation model was relatively reliable, with a prediction accuracy of 90%. This study furthered the existing knowledge of the methods for evaluating vehicle dynamic performance. The proposed overall subjective evaluation model improves the reliability of vehicle dynamic evaluations and offers a theoretical basis for vehicle manufacturers to improve automobile performance.

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Simulation of Driveability in Real-time

Cited by 22 publications

References 1 publication

Objective Rating of the Launch Behavior of Conventional, Hybrid and Electric Vehicles

Objective Rating of the Launch Behavior of Conventional, Hybrid and Electric Vehicles

Modeling and Subjective Evaluation Method of Driveability for Fuel Cell Vehicles

Exploring the Relationships between Subjective Evaluations and Objective Metrics of Vehicle Dynamic Performance

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