Multiobjective optimization of a steering linkage

2018

Sustainability

This paper presents a new design strategy for the passive vibration suppression of a single-cylindrical engine (SCE) through multi-objective evolutionary optimisation. The vibration causes machine damages and human pain, which are unsustainable problemsthat need to be alleviated. Mathematical forced vibration analyses of a single-cylinder engine, including dynamic pressure force due to ignition combustion, are presented. A multi-objective design problem is set to find the shape and size variables of the crank and connecting rod of the engine. The objective functions consist of the minimisation of the crank and connecting rod mass, and the minimisation of vibration response while the SCE is subject to inertial force and pressure force. Moreover, design constraints include crank and rod safety. The design problem is tackled by using an adaptation of a hybrid of multi-objective population-based incremental learning and differential evolution (RPBIL-DE). The optimum results found that the proposed design strategy is a powerful tool for the vibration suppression of SCE.an unconstrained optimisation problem to minimise the transmission of engine vibration due to inertial forces to the supporting structure where the case study is a mounted four-cylinder V-engine rotating at idling speed by an active balancing method. The individual balancing masses and associated phase angles of counter rotating balancing masses were chosen as design variables. Chiou et al. [5] proposed an optimum design in which disk counterweights were added to reduce shaking force and moment of the drag-link drive of mechanical presses. Sleesongsom [6] proposed applying multi-objective optimisation to reduce the engine mount translation and rotation displacements of SCE where the normalised normal constraint method [7], in combination with sequential quadratic programming, is an optimiser. The use of finite element analysis and optimisation codes for connecting rod [8], crankshaft [9], and piston design [10] has been conducted. In addition, the finite element technique has been used to optimise the crankshaft parameters of a single-cylinder motorcycle engine to reduce vibration without considering the gas pressure force inside the combustion chamber [11].The second vibration suppression technique for the engine is vibration isolation. The challenge for designers and engineers is how to properly select vibration isolators in order to minimise the force transmission to the engine base [11][12][13] and the powertrain mounting system [14,15]. Further work focuses on optimisation of engine mounting systems and blocks can be found in References [16][17][18][19][20][21][22][23], while the literature of using meta-heuristic algorithms (MHs) or evolutionary algorithms (EAs) for engine mounting and engine part design can be seen further in Reference [24].Both methods has been studied and used in industry, but the new design technique still lacks development. Recent works of automotive technology have focused on designing the motor of an electric vehicle (EV) t...

Section: Hybrid Rpbil-de For Multi-objective Optimisationmentioning

confidence: 99%

Vibration Suppression of a Single-Cylinder Engine by Means of Multi-objective Evolutionary Optimisation

2018

Sustainability

“…As previously mentioned, only one work by Showers and Lee [19] has defined the steering error in the form called a cornering radius function [32]. Later, a new steering error was compared with the traditional one [17,20], providing better optimization results [33]. Due to the robustness of multi-objective evolutionary algorithms (MOEAs) in solving the steering linkage design, which can perform only once in finding a solution set [17], they can be an alternative choice to gradient-based optimizers.…”

Section: Introductionmentioning

confidence: 99%

“…Later, a new steering error was compared with the traditional one [17,20], providing better optimization results [33]. Due to the robustness of multi-objective evolutionary algorithms (MOEAs) in solving the steering linkage design, which can perform only once in finding a solution set [17], they can be an alternative choice to gradient-based optimizers. It was shown that the performance of such a method for solving minimization of steering error and turning radius is acceptable [33].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective, Reliability-Based Design Optimization of a Steering Linkage

2020

Applied Sciences

Reliability-based design optimization (RBDO) of a mechanism is normally based on the non-probabilistic model, which is viewed as failure possibility constraints in each optimization loop. It leads to a double-loop nested problem that causes a computationally expensive evaluation. Several methods have been developed to solve the problem, which are expected to increase the realization of optimum results and computational efficiency. The purpose of this paper was to develop a new technique of RBDO that can reduce the complexity of the double-loop nested problem to a single-loop. This involves using a multi-objective evolutionary technique combined with the worst-case scenario and fuzzy sets, known as a multi-objective, reliability-based design optimization (MORBDO). The optimization test problem and a steering linkage design were used to validate the performance of the proposed technique. The proposed technique can reduce the complexity of the design problem, producing results that are more conservative and realizable.

“…This equation can be solved by using Freudenstein equation. The second analysis technique is a straight forward and a simple method for position analysis involving the use of trigonometric laws for triangles, e.g., the law of cosine [ 3 , 16 , 17 ], whereas the six-bar linkage for steering mechanism also uses the same technique [ 18 ]. This work proposes a new computing technique for four-bar linkage position analysis by employing the concept of drawing an arbitrary rectangle using two circles.…”

Section: Introductionmentioning

confidence: 99%

Optimal Synthesis of Four-Bar Linkage Path Generation through Evolutionary Computation with a Novel Constraint Handling Technique

Computational Intelligence and Neuroscience

2018

This paper presents a novel constraint handling technique for optimum path generation of four-bar linkages using evolutionary algorithms (EAs). Usually, the design problem is assigned to minimize the error between desired and obtained coupler curves with penalty constraints. It is found that the currently used constraint handling technique is rather inefficient. In this work, we propose a new technique, termed a path repairing technique, to deal with the constraints for both input crank rotation and Grashof criterion. Three traditional path generation test problems are used to test the proposed technique. Metaheuristic algorithms, namely, artificial bee colony optimization (ABC), adaptive differential evolution with optional external archive (JADE), population-based incremental learning (PBIL), teaching-learning-based optimization (TLBO), real-code ant colony optimization (ACOR), a grey wolf optimizer (GWO), and a sine cosine algorithm (SCA), are applied for finding the optimum solutions. The results show that new technique is a superior constraint handling technique while TLBO is the best method for synthesizing four-bar linkages.