Quasi-Static Approach for Mass Estimation of Electric Propelled Vehicles

Marius Miller, Markus Pfeil, Benedikt Reick, Ralph Kennel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper presents an approach for estimating the mass of a vehicle by observing the oscillation behavior of the acceleration signal after a pulse excitation of the system. The short and controlled duration of the excitation pulse used by the vehicle's electric drive merely causes the vehicle to oscillate and does not result in a deeper rolling motion of the wheels, which means that the vehicle remains in a quasi-static range. The dependence of the oscillation on the mass results in a characteristic oscillation profile. A heuristic relation between vehicle mass and damped oscillation frequency for different loading conditions is generated, which can be used to estimate the vehicle mass. It is shown that the oscillation behavior is dependent on the load position and tire pressure of the vehicle. A simple and an extended physical model are proposed to reconstruct the experiments that were conducted beforehand. Subsequently, these models can be used to ensure an efficient process in generating the proposed heuristic relation. To ensure that the model is as realistic as possible, the excitation pulse of the drive train is simulated with the aid of a real-time Hardware in the Loop (HIL) emulator from Typhoon HIL. The electrical model contains a physical model of the inverter and electric machine and is combined with a SIMULINK model of the trailer. The parameter estimation of the unknown spring-damper constants of the real world system is solved by optimizing the model parameters with respect to the real oscillation signals that were measured on an electrified trailer for use in micromobility solutions.

Original languageEnglish
Title of host publicationInternational Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2023
PublisherMesago PCIM GmbH
Pages991-1000
Number of pages10
ISBN (Electronic)9783800760916
DOIs
StatePublished - 2023
Event2023 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2023 - Nuremberg, Germany
Duration: 9 May 202311 May 2023

Publication series

NamePCIM Europe Conference Proceedings
ISSN (Electronic)2191-3358

Conference

Conference2023 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2023
Country/TerritoryGermany
CityNuremberg
Period9/05/2311/05/23

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