Feasibility of Detailed Vehicle Modeling

Bowles, P.; Tiller, Michael; Elmqvist, Hilding; Brück, Dag M.; Mattsson, Sven Erik; Möller, Andreas; Olsson, Hans; Otter, Martin

doi:10.4271/2001-01-0334

Cited by 8 publications

(1 citation statement)

References 2 publications

(1 reference statement)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To determine the optimal choice of powertrain components, simulation is a useful tool for the evaluation of vehicle performance. Several studies have been made to model the vehicle powertrain (Yao et al, 2008;Banerjee and McPhee, 2012;Damiani et al, 2014), fuel consumption (Bowles et al, 2001;Sun et al, 2007;Ehsani et al, 2016), for light duty vehicles (Silva et al, 2006), and for heavy duty applications (Wang et al, 2009). Some authors focussed on the models of forklift trucks.…”

Section: Introductionmentioning

confidence: 99%

Forklift truck performance simulation and fuel consumption estimation

d'Apolito

2019

JEDT

View full text Add to dashboard Cite

Purpose Forklift trucks are generally operated with frequent accelerations and stops, reverse and operations of load handling. This way of operation increases the energy losses and consequently the need for reduction of fuel consumption from forklift customers. This study aims to build a model to replicate the performance of forklifts during real operations and estimate fuel consumption without building a real prototype. Design/methodology/approach AVL Cruise has been used to simulate forklift powertrain and hydraulic circuit. The driving cycles used for this study were in accordance with the standard VDI 2198. Artificial neural networks (ANNs), trained by the results of AVL Cruise simulations, have been used to forecast the fuel consumption for a large set of possible driving cycles. Findings The comparison between simulated and experimental data verified that AVL Cruise model was able to simulate the performance of real forklifts, but the results were only valid for the specified driving cycle. The ANNs, trained by the results of AVL Cruise for a certain number of driving cycles, have been found effective to forecast the fuel consumption of a larger number of driving cycles following the prescriptions of the standard VDI 2198. Originality/value A new method based on ANN, trained by AVL Cruise simulation results, has been introduced to forecast the forklift fuel consumption, reducing the computational time and the cost of experimental tests.

show abstract

Section: Introductionmentioning

confidence: 99%

Forklift truck performance simulation and fuel consumption estimation

d'Apolito

2019

JEDT

View full text Add to dashboard Cite

show abstract

Topological semantics for lumped parameter systems modeling

Wang

Shapiro

2019

Advanced Engineering Informatics

View full text Add to dashboard Cite

Behaviors of many engineering systems are described by lumped parameter models that encapsulate the spatially distributed nature of the system into networks of lumped elements; the dynamics of such a network is governed by a system of ordinary differential and algebraic equations. Languages and simulation tools for modeling such systems differ in syntax, informal semantics, and in the methods by which such systems of equations are generated and simulated, leading to numerous interoperability challenges. Logical extensions of SysML aim specifically at unifying a subset of the underlying concepts in such languages.We propose to unify semantics of all such systems using standard notions from algebraic topology. In particular, Tonti diagrams classify all physical theories in terms of physical laws (topological and constitutive) defined over a pair of dual cochain complexes and may be used to describe different types of lumped parameter systems. We show that all possible methods for generating the corresponding state equations within each physical domain correspond to paths over Tonti diagrams. We further propose a generalization of Tonti diagram that captures the behavior and supports canonical generation of state equations for multi-domain lumped parameter systems.The unified semantics provides a basis for greater interoperability in systems modeling, supporting automated translation, integration, reuse, and numerical simulation of models created in different authoring systems and applications. Notably, the proposed algebraic topological semantics is also compatible with spatially and temporally distributed models that are at the core of modern CAD and CAE systems.

show abstract