Analytical Target Cascading in Automotive Vehicle Design

Kim, Hyung Min; Rideout, Geoff; Papalambros, Panos Y.; Stein, Jeffrey L.

doi:10.1115/1.1586308

Cited by 212 publications

(101 citation statements)

References 12 publications

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“…Analytical target cascading has been used for automotive applications, for example to propagate targets in a chassis design of a sport-utility vehicle [35], to redesign a U.S. class VI truck [36], and more recently, to optimise a hybrid electrical fuel cell vehicle [37] and two commercial vehicle systems [13]. The method has also been used for aerospace applications.…”

Section: Analytical Target Cascadingmentioning

confidence: 99%

Multidisciplinary design optimisation methods for automotive structures

Bäckryd¹,

Ryberg²,

Nilsson³

2017

Int. J. Automot. Mech. Eng.

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Multidisciplinary design optimisation (MDO) can be used as an effective tool to improve the design of automotive structures. Large-scale MDO problems typically involve several groups who must work concurrently and autonomously in order to make the solution process efficient. In this article, the formulations of existing MDO methods are compared and their suitability is assessed in relation to the characteristics of automotive structural applications. Both multi-level and single-level optimisation methods are considered. Multi-level optimisation methods distribute the design process but are complex. When optimising automotive structures, metamodels are often required to relieve the computational burden of detailed simulation models. The metamodels can be created by individual groups prior to the optimisation process, and thus offer a way of distributing work. Therefore, it is concluded that a single-level method in combination with metamodels is the most straightforward way of implementing MDO into the development of automotive structures. If the benefits of multi-level optimisation methods, in a special case, are considered to compensate for their drawbacks, analytical target cascading has a number of advantages over collaborative optimisation, but both methods are possible choices.

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Section: Analytical Target Cascadingmentioning

confidence: 99%

Multidisciplinary design optimisation methods for automotive structures

Bäckryd¹,

Ryberg²,

Nilsson³

2017

Int. J. Automot. Mech. Eng.

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“…Because the product development level focuses only on the suspension for vehicle ride quality improvement, only the targets for front and rear suspension stiffness parameters are treated as variables at the enterprise level. Modeling details of the vehicle chassis composed of front/rear double A-arm suspension and vertical/cornering tire models can be found by Kim et al 24 ATC successfully simulated the vehicle chassis design process based on the targets for handling and ride quality of a sport-utility vehicle. Here a simplified chassis system composed of front/rear suspension subsystems and coil spring components is considered for the engineering product development task (Fig.…”

Section: B Enterprise-driven Multilevel Vehicle Suspension Designmentioning

confidence: 99%

“…In the preceding vehicle chassis design example by ATC, 24 the targets for the chassis system design are given based on experience, that is, fixed target values. In the current formulation, the targets are set based on maximizing the enterprise utility, that is, profit of a firm.…”

Section: Implementation Of Proposed Algorithmmentioning

confidence: 99%

Target Exploration for Disconnected Feasible Regions in Enterprise-Driven Multilevel Product Design

Kim

Kumar²,

Chen³

et al. 2006

AIAA Journal

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Enterprise-level business decisions are linked with engineering product decisions by integrating enterprise utility optimization and engineering design optimization under a hierarchical, multilevel, decision-based design framework. The enterprise problem sets attribute targets, that is, specifications, for engineering product development, which then optimizes product performance within the feasible design space to match the targets with minimum deviations. When the feasible domain imposed by engineering product development is disconnected in the space of attribute targets, an engineering design with the minimum deviation from the targets may not correspond to the design with the maximum utility value, even though the design is a converged solution from the multilevel optimization. To address this issue, a new algorithm is developed, which systematically explores the target space to lead the engineering product development to a feasible and optimal design in the enterprise context. Analytical examples and an automotive suspension design case study are presented to demonstrate the effectiveness of the proposed methodology.

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“…The process formulates and solves a minimum deviation optimization problem for each element of the multi-level system. By solving the element optimization problems sequentially in an iterative manner, ATC aims at minimising discrepancies between the optimal design variable values desired at elements higher in the hierarchy and response values that elements at lower levels can actually deliver [49,52,73,74,79]. In addition, if design variables are shared among some elements at the same level, their required common final optimal value is coordinated by their parent element at the level above.…”

Section: Optimal Design Of Multi-level Systemsmentioning

confidence: 99%

“…[49,52,53], ATC has been used to optimise ride quality and handling performances by considering suspension, tyre, and spring analysis models. Potential incompatibilities among targets and constraints throughout the entire system can be uncovered and the trade-offs involved in achieving system targets under different design scenarios can be quantified.…”

Section: Active Safety and Ride Comfortmentioning

confidence: 99%

Optimization and integration of ground vehicle systems

Gobbi

Haque

Papalambros

et al. 2005

Vehicle System Dynamics

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This article deals with the optimal design of ground vehicles and their subsystems, with particular reference to 'active' safety and comfort. A review of state-of-the-art optimization methods for solving vehicle system design problems, including the integration of electronic controls, is given, thus further encouraging the use of such methods as standard tools for automotive engineers. Particular attention is devoted to the class of methods pertaining to complex system design optimization, as well as approaches for the optimal design of complex systems under uncertainty. Some examples of design optimizations are given in the fields of vehicle system dynamics, powertrain/internal combustion engine design, active safety and ride comfort, vehicle system design and lightweight structures, advanced automotive electronics, and smart vehicles.

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Analytical Target Cascading in Automotive Vehicle Design

Abstract: ABSTRACT

Cited by 212 publications

References 12 publications

Multidisciplinary design optimisation methods for automotive structures

Multidisciplinary design optimisation methods for automotive structures

Target Exploration for Disconnected Feasible Regions in Enterprise-Driven Multilevel Product Design

Optimization and integration of ground vehicle systems

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