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Suspension Optimization Based on Evolutionary Algorithms for Four-wheel Drive and Four-wheel Steered Vehicles

Manuel Schwartz; Lukas Luithle,; Sören Hohmann

A gray-box optimization procedure based on evolutionary algorithms for the initial design of a suspension concept for four wheel independently driven and steered vehicles is developed. With thepresented optimization method, the energy consumption together with state of the art knowledge about the parametrization and design of vehicle suspension systems leads to an optimization setup closely to real world requirements while the vehicle’s topology is exploited.
To this, the modelling presented in [1] is considered as a geometric suspension model. Furthermore, to take advantage of the potential of such vehicles, an autonomous closed-loop setup with integrated motion control is utilized. During the optimization, the chassis parameters with the most impact on energy consumption and driving dynamics, namely camber, caster, scrub radius and the steering axis inclination (SAI) depending on a varying caster angle and SAI in relation to the steering angle, will be focused. Therefore, the geometric arrangement of linkages, further considered as optimization parameters, substitutes certain modelling assumptions, leading to a realistic parametrization regarding mechanical design.
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Zugehörige Institution(en) am KIT Institut für Regelungs- und Steuerungssysteme (IRS)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 15.04.2021
Sprache Englisch
Identifikator KITopen-ID: 1000131517
Erschienen in SAE WCX Digital Summit
Veranstaltung SAE WCX Digital Summit (2021), Online, 13.04.2021 – 15.04.2021
Bemerkung zur Veröffentlichung SAE Technical Paper 2021-01-0933, 2021, 0148-7191
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