Robust multi-objective design of suspension systems

This thesis presents a robust multi-objective optimal design of four-degree-of-freedom passive and semi-active suspension systems. The passive suspension system is used in a racing car and the semi-active suspension is implemented on a passenger car. Mathematical models of the commercial and racing vehicle suspension systems are used in the computer simulations. A robust multi-objective design of the suspension systems is carried out by considering the minimization of three objectives: passenger’s head acceleration (HA), suspension deflection (SD), and tire deflection (TD). The first objective is concerned with the passenger’s health and comfort. The suspension stroke is described by SD and the tire holding is characterized by TD. The optimal design of the passive suspension involves tuning the coefficients of the sprung spring and damper, tire stiffness, and inertance of the inerter. Suspension systems’ parametric variations are very common and cannot be avoided in practice. To this end, a robust multi-objective optimization method that takes into consideration small changes in the design parameters should be considered. Unlike traditional multi-objective optimization problems where the focus is placed on finding the global Pareto-optimal solutions which express the optimal trade-offs among design objectives, the robust multi-objective optimization algorithms are concerned with robust solutions that are less sensitive to perturbations of decision variables. As a result, the mean effective values of the fitness functions are used as design objectives. Constraints on the design parameters and goals are applied. Numerical simulations show that the robust multi-objective design (RMOD) is very effective and guarantees a robust behavior as compared to that of the classical multi-objective design (MOD). The results also show that the robust region is inside the feasible search space and avoids all of its boundaries. The decision parameter space of the semi-active suspension includes both passive and active components. The passive components include the stiffness of the sprung spring, damping coefficient of the shock absorber, and stiffness of the tire. The active elements are the design details of the LQR algorithm. During the design, global sensitivity analysis is conducted to determine the elements of the suspension system that have high impact on the design objectives. The mass of the passenger’s head and upper body, the mass of the passenger’s lower body and cushion, passenger and cushion’s elastic properties, and the sprung mass of the vehicle are selected for the sensitivity analysis. Results show that the design goals are more sensitive to the variations in the sprung mass than the other parameters. As a result, parametric variations in the sprung mass of the vehicle and passive elements of the suspension system are considered. Similar to the design of the passive suspension, the mean effective values of SD, TD, and HA are used as design objectives. Also, constraints are applied on the objectives in compliance with the requirements of ISO 2631-1 on the design of car suspension systems. The optimization problem is solved by the NSGA-II (non-dominated sorting genetic algorithm) and robust Pareto front and set are obtained

Multi-Dimensional Assessment of Transit System Efficiency and Incentive-based Subsidy Allocation

Over the past several decades, contending with traffic congestion and air pollution has emerged as one of the imperative issues across the world. Development of a transit-oriented urban transport system has been realized by an increasing number of countries and administrations as one of the most effective strategies for mitigating congestion and pollution problems. Despite the rapid development of public transportation system, doubts regarding the efficiency of the system and financing sustainability have arisen. Significant amount of public resources have been invested into public transport; however complaints about low service quality and unreliable transit system performance have increasingly arisen from all walks of life. Evaluating transit operational efficiency from various levels and designing incentive-based mechanisms to allocate limited subsidies/resources have become one of the most imperative challenges faced by responsible authorities to sustain the public transport system development and improve its performance and levels of service. After a comprehensive review of existing literature, this dissertation aims to develop a multi-dimensional framework composed of a series of robust multi-criteria evaluation models to assess the operational and financial performance of transit systems at various levels of application (i.e. region/city level, operator level, and route level). It further contributes to bridging the gap between transit efficiency evaluation and the subsequent subsidy allocation by developing a set of incentive-based resource allocation models taking various levels of operational and financial efficiencies into consideration. Case studies using real-world transit data will be performed to validate the performance and applicability of the proposed models

A Human Driver Model for Autonomous Lane Changing in Highways: Predictive Fuzzy Markov Game Driving Strategy

This study presents an integrated hybrid solution to mandatory lane changing problem to deal with accident avoidance by choosing a safe gap in highway driving. To manage this, a comprehensive treatment to a lane change active safety design is proposed from dynamics, control, and decision making aspects. My effort first goes on driver behaviors and relating human reasoning of threat in driving for modeling a decision making strategy. It consists of two main parts; threat assessment in traffic participants, (TV s) states, and decision making. The first part utilizes an complementary threat assessment of TV s, relative to the subject vehicle, SV , by evaluating the traffic quantities. Then I propose a decision strategy, which is based on Markov decision processes (MDPs) that abstract the traffic environment with a set of actions, transition probabilities, and corresponding utility rewards. Further, the interactions of the TV s are employed to set up a real traffic condition by using game theoretic approach. The question to be addressed here is that how an autonomous vehicle optimally interacts with the surrounding vehicles for a gap selection so that more effective performance of the overall traffic flow can be captured. Finding a safe gap is performed via maximizing an objective function among several candidates. A future prediction engine thus is embedded in the design, which simulates and seeks for a solution such that the objective function is maximized at each time step over a horizon. The combined system therefore forms a predictive fuzzy Markov game (FMG) since it is to perform a predictive interactive driving strategy to avoid accidents for a given traffic environment. I show the effect of interactions in decision making process by proposing both cooperative and non-cooperative Markov game strategies for enhanced traffic safety and mobility. This level is called the higher level controller. I further focus on generating a driver controller to complement the automated car’s safe driving. To compute this, model predictive controller (MPC) is utilized. The success of the combined decision process and trajectory generation is evaluated with a set of different traffic scenarios in dSPACE virtual driving environment. Next, I consider designing an active front steering (AFS) and direct yaw moment control (DYC) as the lower level controller that performs a lane change task with enhanced handling performance in the presence of varying front and rear cornering stiffnesses. I propose a new control scheme that integrates active front steering and the direct yaw moment control to enhance the vehicle handling and stability. I obtain the nonlinear tire forces with Pacejka model, and convert the nonlinear tire stiffnesses to parameter space to design a linear parameter varying controller (LPV) for combined AFS and DYC to perform a commanded lane change task. Further, the nonlinear vehicle lateral dynamics is modeled with Takagi-Sugeno (T-S) framework. A state-feedback fuzzy H∞ controller is designed for both stability and tracking reference. Simulation study confirms that the performance of the proposed methods is quite satisfactory

Selected Papers from IEEE ICASI 2019

The 5th IEEE International Conference on Applied System Innovation 2019 (IEEE ICASI 2019, https://2019.icasi-conf.net/), which was held in Fukuoka, Japan, on 11–15 April, 2019, provided a unified communication platform for a wide range of topics. This Special Issue entitled “Selected Papers from IEEE ICASI 2019” collected nine excellent papers presented on the applied sciences topic during the conference. Mechanical engineering and design innovations are academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs. Technological innovation by mechanical engineering includes information technology (IT)-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology. These new technologies that implant intelligence in machine systems represent an interdisciplinary area that combines conventional mechanical technology and new IT. The main goal of this Special Issue is to provide new scientific knowledge relevant to IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology

Planning and operation objectives of public electric vehicle charging infrastructures: a review

Planning public electric vehicle (EV) charging infrastructure has gradually become a key factor in the electrification of mobility and decarbonization of the transport sector. In order to achieve a high level of electrification in mobility, in recent years, different studies have been presented, proposing novel practices and methodologies for the planning and operation of electric vehicles charging infrastructure. In this paper, the authors present an up-to-date analysis of the existing literature in this research field, organized by considering the perspectives and objectives of the principal actors/operators of the EV public charging infrastructure value chain. Among these actors, the electric vehicle, the charging operators and service providers, and the power system infrastructure (transmission and distribution system) are analyzed in depth. By classifying the reviewed literature based on this manifold viewpoints approach, this paper aims to facilitate researchers and technology developers in exploring the state-of-the-art methodologies for each actor’s perspective, and identify conflicting interests and synergies in charging infrastructure operation and planning.The authors would like to thank the Research Council of Norway and industry partners for the support in writing this paper under project 295133/E20FuChar—Grid and Charging Infrastructure of the Future https://prosjektbanken.forskningsradet.no/en/project/FORISS/295133?Kilde=F ORISS&distribution=Ar&chart=bar&calcType=funding&Sprak=no&sortBy=score&sortOrder=desc& resultCount=30&offset=0&Fritekst=fuchar&source=FORISS&projectId=295133 (accessed on 23 June 2023). The authors gratefully acknowledge Michele Garau, Bendik Nybakk Torsæter, and Daniel Mota from SINTEF Energy Research for their contribution to the conceptualization and review of the article. The work of Andreas Sumper was supported by the Catalan Institution for Research and Advanced Studies (ICREA) Academia Program.Postprint (published version

Preview-based techniques for vehicle suspension control: a state-of-the-art review

Abstract Automotive suspension systems are key to ride comfort and handling performance enhancement. In the last decades semi-active and active suspension configurations have been the focus of intensive automotive engineering research, and have been implemented by the industry. The recent advances in road profile measurement and estimation systems make road-preview-based suspension control a viable solution for production vehicles. Despite the availability of a significant body of papers on the topic, the literature lacks a comprehensive and up-to-date survey on the variety of proposed techniques for suspension control with road preview, and the comparison of their effectiveness. To cover the gap, this literature review deals with the research conducted over the past decades on the topic of semi-active and active suspension controllers with road preview. The main formulations are reported for each control category, and the respective features are critically analysed, together with the most relevant performance indicators. The paper also discusses the effect of the road preview time on the resulting system performance, and identifies control development trends

Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design

Designing complex engineering systems, such as an aircraft or an aero-engine, is immensely challenging. Formal Systems Engineering (SE) practices are widely used in the aerospace industry throughout the overall design process to minimise the overall design effort, corrective re-work, and ultimately overall development and manufacturing costs. Incorporating the needs and requirements from customers and other stakeholders into the conceptual and early design process is vital for the success and viability of any development programme. This paper presents a formal methodology, the Value-Driven Design (VDD) methodology that has been developed for collaborative and iterative use in the Extended Enterprise (EE) within the aerospace industry, and that has been applied using the Concept Design Analysis (CODA) method to map captured Customer Needs (CNs) into Engineering Characteristics (ECs) and to model an overall ‘design merit’ metric to be used in design assessments, sensitivity analyses, and engineering design optimisation studies. Two different case studies with increasing complexity are presented to elucidate the application areas of the CODA method in the context of the VDD methodology for the EE within the aerospace secto

Neurofuzzy controller based full vehicle nonlinear active suspension systems

To design a robust controller for active suspension systems is very important for guaranteeing the riding comfort for passengers and road handling quality for a vehicle. In this thesis, the mathematical model of full vehicle nonlinear active suspension systems with hydraulic actuators is derived to take into account all the motions of the vehicle and the nonlinearity behaviours of the active suspension system and hydraulic actuators. Four robust control types are designed and the comparisons among the robustness of those controllers against different disturbance types are investigated to select the best controller among them. The MATLAB SIMULINK toolboxes are used to simulate the proposed controllers with the controlled model and to display the responses of the controlled model under different types of disturbance. The results show that the neurofuzzy controller is more effective and robust than the other controller types. The implementation of the neurofuzzy controller using FPGA boards has been investigated in this work. The Xilinx ISE program is employed to synthesis the VHDL codes that describe the operation of the neurofuzzy controller and to generate the configuration file used to program the FPGA. The ModelSim program is used to simulate the operation of the VHDL codes and to obtain the expected output data of the FPGA boards. To confirm that FPGA the board used as the neurofuzzy controller system operated as expected, a MATLAB script file is used to compare the set of data obtained from the ModelSim program and the set of data obtained from the MATLAB SIMULINK model. The results show that the FPGA board is effective to be used as a neurofuzzy controller for full vehicle nonlinear active suspension systems. The active suspension system has a great performance for vibration isolation. However the main drawback of the active suspension is that it is high energy consumptive. Therefore, to use this suspension system in the proposed model, this drawback should be solved. Electromagnetic actuators are used to convert the vibration energy that arises from the rough road to useful electrical energy to reduce the energy consumption by the active suspension systems. The results show that the electromagnetic devices act as a power generator, i.e. the vibration energy excited by the rough road surface has been converted to a useful electrical energy supply for the actuators. Furthermore, when the nonlinear damper models are replaced by the electromagnetic actuators, riding comfort and the road handling quality are improved. As a result, two targets have been achieved by using hydraulic actuators with electromagnetic suspension systems: increasing fuel economy and improving the vehicle performance