Modeling of Electric Vehicles for Driveability Control Applications

For the last two decades, an extensive transition in automotive X-in-the-loop activities from isolated electronic control units to real-time related, geographically distributed validation tasks has occurred. Benefits are strengthening frontloading, enabling concurrent engineering and reducing prototypes and testing efforts. As a downside, comprehensive system understanding and adequate simulation models must be provided. New technological trends like software-over-the-air-updates denote a continuous validation process even after the start of production. The present review focuses on the virtual validation of vehicle longitudinal dynamics. This exemplary field of application receives more and more attention as electrification of the vehicle powertrain accelerates, and this property directly influences the vehicle DNA. A systematic review process based on the PRISMA workflow has been conducted, focusing on drivabilityrelated powertrain applications. The investigation reveals the following trends: First, increasing complexity of virtualisation methods and models for validation activities influenced by vehicle-to-everything and geographically distributed development. Second, missing standards for virtual validation and proof of representativeness for combined real-virtual testing. In addition, many studies only contemplate the advantages of hardware-in-the-loop-driven development, disregarding crucial limitations and risks for such approaches. In conclusion, there is no longer the question of whether to validate virtually but how to comprehensible realise virtual validation.

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Methods for Virtual Validation of Automotive Powertrain Systems in Terms of Vehicle Drivability—A Systematic Literature Review

Schmidt

Büttner

Prokop

2023

IEEE Access

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Toward better drivability: Investigating user preferences for tip-in acceleration profiles in electric vehicles

Kim,

Yang

2024

PLoS ONE

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Vehicle drivability, defined as the smooth operation and stability of a vehicle in response to driver inputs, significantly influences the performance of passenger cars. Among various driving conditions, tip-in acceleration is one of the most frequently encountered and crucial factors affecting drivability. This study investigates preferred longitudinal acceleration profiles for electric vehicles through subjective evaluations obtained from on-road tests. Five distinctive acceleration profiles were designed for tip-in conditions and evaluated by 15 highly experienced experts using the paired comparison method. Evaluations were conducted across three scenarios: light tip-in at 30 km/h, middle tip-in at 30 km/h, and middle tip-in at 60 km/h. Experimental results revealed distinct preferences based on driving conditions. For light tip-in at 30 km/h, drivers favored linear acceleration profiles with smaller jerk magnitudes and kurtosis. Conversely, for middle tip-in conditions at both 30 and 60 km/h, drivers preferred acceleration profiles exhibiting rapid initial acceleration followed by a smooth transition. However, at 60 km/h, a preference for higher jerk and steeper gradients was observed. Correlation analyses provided insights into the relationship between subjective preferences and dynamic characteristics of acceleration profiles. This study contributes practical guidance for designing optimal acceleration profiles aligned with driver preferences, thereby enhancing drivability and overall user experience in electric vehicles.

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Modeling of Electric Vehicles for Driveability Control Applications

Cited by 2 publications

References 2 publications

Methods for Virtual Validation of Automotive Powertrain Systems in Terms of Vehicle Drivability—A Systematic Literature Review

Methods for Virtual Validation of Automotive Powertrain Systems in Terms of Vehicle Drivability—A Systematic Literature Review

Toward better drivability: Investigating user preferences for tip-in acceleration profiles in electric vehicles

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