Suspension vertical and longitudinal modeling and parameter estimation for ride comfort assessment

dc.contributor.authorPai, Sumanth
dc.contributor.authorGamez Berral, Miguel
dc.contributor.departmentChalmers tekniska högskola / Institutionen för mekanik och maritima vetenskapersv
dc.contributor.departmentChalmers University of Technology / Department of Mechanics and Maritime Sciencesen
dc.contributor.examinerJacobson, Bengt
dc.contributor.supervisorDaniel, Ajay
dc.date.accessioned2025-11-04T15:44:07Z
dc.date.issued2025
dc.date.submitted
dc.description.abstractRide comfort is a key vehicle attribute, strongly influenced by suspension design and vital to both perceived quality and long-distance comfort. Setting meaningful requirements early in development is challenging, as engineers must work with aggregated vehicle parameters. Existing high fidelity simulation tools, while powerful, typically require detailed component data, limiting their usefulness in early-stage development. At the same time, increasing pressure from electrification and competition makes it more important than ever to define clear ride requirements early, to downstream effectively. To address this challenge, this thesis investigates whether a simplified modeling approach can aid early-stage ride comfort target setting, focusing specifically on impact harshness. A modular quarter-car model was developed that includes both vertical and longitudinal dynamics, along with a simplified tire model to represent force distribution in both directions. Tailored for the concept phase, the model was structured around system-level inputs rather than detailed component data. To capture the relevant high-frequency dynamics, vertical parameters were identified using 4-poster shaker rig data through nonlinear optimization. Kinematics & Compliance (K&C) rig data supported both the estimation process and partial parameterization of the longitudinal model. Data from three different vehicles were used to ensure the model’s robustness across varying suspension setups. The model was evaluated by simulating a cleat test and comparing its outputs with corresponding test track measurements. The nonlinear optimization of vertical parameters allowed the model to capture ground-to-body acceleration with an average fit exceeding 80 percent across all vehicle axles. Impact harshness metrics predicted from cleat simulations showed deviations of up to roughly 50 percent across different axles, with some larger discrepancies in specific cases. These differences were primarily linked to the simplified tire model’s limited ability to capture high-frequency dynamics.
dc.identifier.coursecodeMMSX30
dc.identifier.urihttp://hdl.handle.net/20.500.12380/310707
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectSuspension modeling
dc.subjectQuarter-Car
dc.subjectlongitudinal suspension
dc.subjectNVH
dc.subjectride comfort
dc.subjectimpact harshness
dc.subjectShaker rig
dc.subjectK&C rig
dc.subjectparameter identification
dc.titleSuspension vertical and longitudinal modeling and parameter estimation for ride comfort assessment
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster's Thesisen
dc.type.uppsokH
local.programmeMobility engineering (MPMOB), MSc

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