Crashworthy structures for future vehicle architecture of autonomous pods and heavy quadricycles on public roads: A review

Author(s):  
Andrew Harrison ◽  
Jesper Christensen ◽  
Christophe Bastien ◽  
Stratis Kanarachos

With the development and deployment of lightweight vehicles to the market, inclusive of autonomous pods, a review of advanced crashworthy structures and the design methodology has been conducted as it is thought that super-lightweight vehicles may pose significant risk to the occupants if they are involved in a crash. It is suggested that tests should include oblique and multiple velocity impacts to cater for the effects of assisted driving systems of future vehicles. A review of current crash structures and design methodologies revealed that the most recent research do not cater to multiple crash scenarios, nor a shorter crush allowance, therefore resulting in poor crashworthiness performance. In addition, the arbitrary seat positioning shown in autonomous pods’ concepts vastly increases the risk to occupants. Greater enhancements to passive crashworthiness are imperative. To this end, functionally graded vehicle structures should be designed as it has been found that these can provide optimized solutions. Research into nonlinear optimization methods for computationally expensive problems will become central to this.

2019 ◽  
Vol 7 (4) ◽  
pp. 5-8
Author(s):  
Linar Sabitov ◽  
Ilnar Baderddinov ◽  
Anton Chepurnenko

The article considers the problem of optimizing the geometric parameters of the cross section of the belts of a trihedral lattice support in the shape of a pentagon. The axial moment of inertia is taken as the objective function. Relations are found between the dimensions of the pentagonal cross section at which the objective function takes the maximum value. We introduce restrictions on the constancy of the consumption of material, as well as the condition of equal stability. The solution is performed using nonlinear optimization methods in the Matlab environment.


2021 ◽  
Vol 65 (1) ◽  
pp. 42-52
Author(s):  
Hamed Keshmiri Neghab ◽  
Hamid Keshmiri Neghab

The use of DC motors is increasingly high and it has more parameters which should be normalized. Now the calibration of each parameters is important for each motor, because it affects in its performance and accuracy. A lot of researches are investigated in this area. In this paper demonstrated how to estimate the parameters of a Nonlinear DC Motor using different Nonlinear Optimization techniques of fitting parameters to model, that called model calibration. First, three methods for calibration of a DC motor are defined, then unknown parameters of the mathematical model with the nonlinear optimization techniques for the fitting routines and model calibration process, are identified. In addition, three optimization techniques such as Levenberg-Marquardt, Constrained Nonlinear Optimization and Gauss-Newton, are compared. The goal of this paper is to estimate nonlinear parameters of a DC motor under uncertainty with nonlinear optimization methods by using LabVIEW software as an industrial software and compare the nonlinear optimization methods based on position, velocity and current. Finally, results are illustrated and comparison between these methods based on the results are made.


1992 ◽  
Vol 28 (2) ◽  
pp. 1581-1584 ◽  
Author(s):  
R.R. Saldanha ◽  
S. Pelissier ◽  
K. Kadded ◽  
Y.P. Yonnet ◽  
J.-L. Coulomb

Author(s):  
Jose´ C. F. Teixeira ◽  
Senhorinha F. C. F. Teixeira ◽  
Aˆngela M. E. Silva

Amongst the various alternatives for the combined production of heat and power, the systems based on a gas turbine are becoming increasingly attractive. In addition to the high thermal efficiency, they can also operate on a wide variety of fuels. The basic configuration of a simple cogeneration system consisting of a gas turbine and a heat recovery steam generator has been used to illustrate the application of nonlinear optimization numerical methods as a tool to evaluate and optimize complex energy systems. The problem was formulated as the minimization of costs as the objective function, subject to the constraints imposed by the physical and thermodynamic quantities. Two numerical nonlinear optimization methods with constraints have been tested using a Fortran code and the MATLAB® environment. The model has been evaluated on a real cogeneration plant consisting of a gas turbine heat recovery system of a local textile factory.


2017 ◽  
Vol 33 (2) ◽  
pp. 138-168 ◽  
Author(s):  
Ingmar Vierhaus ◽  
Armin Fügenschuh ◽  
Robert Gottwald ◽  
Stefan Grösser

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