Suspension control strategy for a fully electrified vehicle

Juan C. Tudon-Martinez, Sebastien Varrier, Ruben Morales-Menendez, Ricardo Ramirez-Mendoza

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

The design of chassis for a truck considers a wide set of conditions in which load and unload are the most typical variety. For years, flat ride rules have been applied to achieve comfort, by providing tuning rules in the suspension as today. For an electric vehicle however, the weight distribution is different as a result of power train and batteries. A suspension control strategy is proposed in a full size pick-up truck using magneto-rheological dampers. As a first principle, the estimation of the frequency of the road profile allows the control of comfort and road holding in normal driving situations (straight roads). This strategy includes the coupling joints among the four-wheel stations of the truck and it allows the control of vertical forces in order to minimize the chassis vertical acceleration. A second principle, it uses the continuous measurement of the steering wheel to configure the four semi-active damping forces in order to reduce the wheel tramp, wheel hop, front-end dive, and other causes of vehicle instability under risk driving conditions. Simulation results in CarSim™ of a full prototype show that the suspension performance of the new fully electrified truck is better in comfort (reduction up to 60% in the chassis vertical acceleration) and handling (reduction around 5% in the vehicle slip angle) than the original truck (before its modification).

Original languageEnglish
Pages1469-1474
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2013
Externally publishedYes
Event2013 European Control Conference, ECC 2013 -
Duration: 1 Dec 2013 → …

Conference

Conference2013 European Control Conference, ECC 2013
Period1/12/13 → …

Bibliographical note

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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