Formula SAE Interchangeable Independent Rear Suspension Design

The Suspension Solutions design team has completely designed built and tested an independent rear suspension system for the 2008 FSAE car. The car currently features a solid rear axle, and the task of converting it to incorporate an interchangeable rear suspension has been undertaken in order to quantify the advantages and disadvantages of each design philosophy. The car has been properly tested with both the solid axle and independent rear suspension side-by-side, however more testing is suggested. After pushing both setups to their limits on a 50ft diameter skid pad, the test results were quantified, and a final comparison between the two design philosophies was tabulated. From our limited testing we can easily conclude that an IRS FSAE car, at minimum, can match the performance of the previous solid axle setup, while being 22lbs heavier. We suspect its performance advantage to become apparent with additional testing however. More subjectively, it was found that the IRS handled more predictably and was easier for novice drivers to control and drive. Our results help quantify the advantages and disadvantages of each system and can be used by future FSAE teams to make more informed design decisions. Our independent rear suspension design includes an unequal length A-Arm configuration, new rear uprights, spindles and hubs, a Torsen differential, and an additional steel space frame to connect all of the listed components to the CP08 chassis. Our initial analysis shows that a performance edge between the two competing systems is dependent on the overall weight of each system and our preliminary testing results help confirm this analysis

Electric Vehicle Efficient Power and Propulsion Systems

Vehicle electrification has been identified as one of the main technology trends in this second decade of the 21st century. Nearly 10% of global car sales in 2021 were electric, and this figure would be 50% by 2030 to reduce the oil import dependency and transport emissions in line with countries’ climate goals. This book addresses the efficient power and propulsion systems which cover essential topics for research and development on EVs, HEVs and fuel cell electric vehicles (FCEV), including: Energy storage systems (battery, fuel cell, supercapacitors, and their hybrid systems); Power electronics devices and converters; Electric machine drive control, optimization, and design; Energy system advanced management methods Primarily intended for professionals and advanced students who are working on EV/HEV/FCEV power and propulsion systems, this edited book surveys state of the art novel control/optimization techniques for different components, as well as for vehicle as a whole system. New readers may also find valuable information on the structure and methodologies in such an interdisciplinary field. Contributed by experienced authors from different research laboratory around the world, these 11 chapters provide balanced materials from theorical background to methodologies and practical implementation to deal with various issues of this challenging technology. This reprint encourages researchers working in this field to stay actualized on the latest developments on electric vehicle efficient power and propulsion systems, for road and rail, both manned and unmanned vehicles

Quantitative Performance Assessment of LiDAR-based Vehicle Contour Estimation Algorithms for Integrated Vehicle Safety Applications

Many nations and organizations are committing to achieving the goal of `Vision Zero\u27 and eliminate road traffic related deaths around the world. Industry continues to develop integrated safety systems to make vehicles safer, smarter and more capable in safety critical scenarios. Passive safety systems are now focusing on pre-crash deployment of restraint systems to better protect vehicle passengers. Current commonly used bounding box methods for shape estimation of crash partners lack the fidelity required for edge case collision detection and advanced crash modeling. This research presents a novel algorithm for robust and accurate contour estimation of opposing vehicles. The presented method is evaluated via a developed framework for key performance metrics and compared to alternative algorithms found in literature

Stability analysis and speed control of brushless DC motor based on self-ameliorate soft switching control methods

In recent years, electric vehicles are the large-scale spread of the transportation field has led to the emergence of brushless direct current (DC) motors (BLDCM), which are mostly utilized in electrical vehicle systems. The speed control of a BLDCM is a subsystem, consisting of torque, flux hysteresis comparators, and appropriate switching logic of an inverter. Due to the sudden load torque variation and improper switching pulse, the speed of the BLDCM is not maintained properly. In recent research, the BLDC current control method gives a better way to control the speed of the motor. Also, the rotor position information should be the need for feedback control of the power electronic converters to varying the appropriate pulse width modulation (PWM) of the inverter. The proposed optimization work controls the switching device to manage the power supply BLDCM. In this proposed self-ameliorate soft switching (SASS) system is a simple and effective way for BLDC motor current control technology, a proposed control strategy is intended to stabilize the speed of the BLDCM at different load torque conditions. The proposed SASS system method is analyzing hall-based sensor values continuously. The suggested model is simulated using the MATLAB Simulink tool, and the results reveal that the maximum steady-state error value achieved is 4.2, as well as a speedy recovery of the BLDCM's speed

Suspension parameters analysis for different track conditions

Dissertação de mestrado integrado em Engenharia Mecânica (área de especialização em Sistemas Mecatrónicos)Este trabalho, aqui apresentado, tem como objetivo o estudo do comportamento do sistema de suspensão de um veículo ao atravessar estradas com obstáculos, como lombas ou buracos. Para atingir este objetivo, uma vasta revisão literária foi feita. Sendo este um tópico extenso, três tipos de revisão foram feitos. Primeiro, a um estudo global à tecnologia usava hoje em dia em pneus e nos sistemas de suspensão de veículos foi compilado. Uma breve menção à cinemática de veículos é empreendida. De seguida, a dinâmica do contacto pneu/solo é sistematicamente explanada, para compreender os diversos modelos de pneu (força) existentes. Adicionalmente, os conceitos fundamentais da análise da dinâmica multicorpo são expostos para justificar a modelação do veículo como um sistema multicorpo. Com toda a teoria apresentada, os conceitos previamente explicados são aplicados na prática para a formulação de um método que visa estimar a trajetória de um veículo atravessando uma qualquer estrada. O primeiro passo a executar é a escolha do modelo de pneu a utilizar. Percebe-se que se deve usar modelos matemáticos, culminando na escolha da Magic Formula. Os passos seguintes consistem na introdução de uma metodologia, que estima o contacto entre um pneu e o solo, para simular as dinâmicas pneu/solo de um veículo. Dois métodos diferentes são expostos: o primeiro para estradas completamente planas, sem obstáculos; o segundo, para estradas com obstáculos, como lombas ou buracos. Este modelo é posteriormente inserido num programa de análise das dinâmicas multicorpo, MUBODYNA3D, e diversas simulações são realizadas. Estas simulações começam pela definição do veículo como um sistema multicorpo, com corpos conectados por juntas cinemáticas. As primeiras simulações são realizadas numa estrada plana para validar os modelos e metodologias previamente criadas. O integrador, que integra os resultados das equações do movimento para prever a trajetória, é refinado. Finalmente, simulações com estradas com obstáculos são geradas. Por fim, os resultados dessas simulações são discutidos, percebendo-se que apresentam um valor inesperado. Ao atravessar um obstáculo, as rodas perdem o contacto com a superfície, provocando a descolagem do carro. No entanto, é concluído que a análise de sistemas multicorpo é de extrema relevância para a simulação de realidades complexas, produzindo resultados precisos.This work, hereby presented, has a primary target of studying the behaviour of a road vehicle’s suspension system, while it is traversing roads with big obstacles, such as potholes or speed bumps/humps. To accomplish this task, a broad literature review was made. Since this is an extensive topic, three types of review were made. Firstly, an overview of the state-of-the-art technology used in tires and suspension systems nowadays is compiled. A brief mention to vehicle kinematics is also made. Then, the dynamics of the contact tire/road are systematically explained, in order to understand the diverse tire force models that exist. Lastly, a rundown of the fundamental concepts of multibody dynamics analysis is exposed to substantiate the modelling of a vehicle as a multibody system later on. With the theory behind, all concepts previously abridged are put to practice, into the formulation of a method to estimate the trajectory of a vehicle crossing a certain road. The first step to execute this is to choose the tire force model to use. It is seen that, in this case, the mathematical models are the best choice, which culminates in the selection of the Magic Formula model. The following steps consist of introducing the contact estimation methodology created to simulate the tire/road dynamics of a vehicle. Two different methods are exposed: the first for fully flat roads, with no obstacles; the second, for road that possess obstacles, like bumps for example. This model is then inserted into a multibody dynamics analysis program, MUBODYNA3D, and some forward dynamic simulations are performed. These simulations start with the definition of the vehicle as a multibody system, with bodies connected by kinematic joints. The first simulations are performed in flat roads to validate the models and methodologies created. The solver, that integrates the results of the equations of motion to predict the trajectory, are then refined. Finally, simulations using roads with obstacles are conducted and the results analysed. In the end, the simulations result in some unexpected behaviour from the vehicle. While crossing an obstacle, it tends to lose contact with the surface and, thus, lift off the road, which is unrealistic. Nonetheless, it is concluded that multibody systems analysis is extremely important to simulate and analyse complex realities, with precise results

Reitinsuunnittelu määrätyssä järjestyksessä tehtäville peltotöille usean työkoneen yhteistyönä

Coverage path planning is the task of finding a collision free path that passes over every point of an area or volume of interest. In agriculture, the coverage task is encountered especially in the process of crop cultivation. Several tasks are performed on the field, one after the other, during the cultivation cycle. Cooperation means that multiple agents, in this case vehicles, are working together towards a common goal. Several studies consider the problem where a single task is divided and assigned among the agents. In this thesis, however, the vehicles have different tasks that are sequentially dependent, that is, the first task must be completed before the other. The tasks are performed simultaneously on the same area. The literature review suggests that there is a lack of previous research on this topic. The objective of this thesis was to develop an algorithm to solve the cooperative coverage path planning problem for sequentially dependent tasks. A tool chain that involves Matlab, Simulink and Visual Studio was adapted for the development and testing of the solution. A development and testing architecture was designed including a compatible interface to a simulation and a real-life test environment. Two different algorithms were implemented based on the idea of computing short simultaneous paths at a time and scheduling them in real-time. The results were successfully demonstrated in a real-life test environment with two tractors equipped with a disc cultivator and a seeder. The objective was to sow the test area. The test drives show that with the algorithms that were developed in this thesis it is possible to perform two sequentially dependent agricultural coverage tasks simultaneously on the same area.Kattavassa reitinsuunnittelussa yritetään löytää polku, jonka aikana määritelty ala tai tilavuus tulee käytyä läpi niin että alueen jokainen piste on käsitelty. Maataloudessa tämä tehtävä on merkityksellinen erityisesti peltoviljelyssä. Useita peltotöitä suoritetaan yksi toisensa jälkeen samalla alueella viljelyvuoden aikana. Useissa tutkimuksissa käsitellään yhteistyönä tehtävää reitinsuunnittelua, jossa yksi tehtävä on jaettu osiin ja osat jaetaan useiden tekijöiden kuten robottien kesken. Tässä diplomityössä peltotyökoneilla on kuitenkin omat erilliset tehtävänsä, joilla on määrätty järjestys, eli niiden suorittaminen riippuu työjärjestyksestä. Työkoneet työskentelevät samanaikaisesti samalla alueella. Diplomityössä tehty kirjallisuuskatsaus viittaa siihen, että vastaavaa aihetta ei ole aiemmin tutkittu. Tämän diplomityön tavoitteena on kehittää algoritmi, jolla voidaan toteuttaa reitinsuunnittelu määrätyssä järjestyksessä tehtäville peltotöille usean peltotyökoneen yhteistyönä. Algoritmikehitystä ja testausta varten suunniteltiin yhtenäinen rajapinta, jolla algoritmia voitaisiin testata sekä simulaatiossa että todellisessa testitilanteessa. Algoritmikehityksessä käytettiin työkaluina Matlab, Simulink ja Visual Studio -ohjelmia. Työssä toteutettiin kaksi algoritmia, jotka perustuvat samaan ideaan: suunnitellaan kerrallaan kaksi lyhyttä samanaikaista polkua, jotka ajoitetaan reaaliajassa. Algoritmeja testattiin todellisessa testiympäristössä kahden työkoneen yhteistyönä, kun tavoitteena on kylvää koko testialue. Ensimmäinen työvaihe suoritettiin lautasmuokkaimella ja toinen kylvökoneella. Testiajot osoittavat, että diplomityössä kehitetyillä algoritmeilla voidaan ohjata kahden toisistaan riippuvaisen peltotyön toteutus samanaikaisesti samalla peltoalueella

Enhanced vision-based localization and control for navigation of non-holonomic omnidirectional mobile robots in GPS-denied environments

New Zealand’s economy relies on primary production to a great extent, where use of the technological advances can have a significant impact on the productivity. Robotics and automation can play a key role in increasing productivity in primary sector, leading to a boost in national economy. This thesis investigates novel methodologies for design, control, and navigation of a mobile robotic platform, aimed for field service applications, specifically in agricultural environments such as orchards to automate the agricultural tasks. The design process of this robotic platform as a non-holonomic omnidirectional mobile robot, includes an innovative integrated application of CAD, CAM, CAE, and RP for development and manufacturing of the platform. Robot Operating System (ROS) is employed for the optimum embedded software system design and development to enable control, sensing, and navigation of the platform. 3D modelling and simulation of the robotic system is performed through interfacing ROS and Gazebo simulator, aiming for off-line programming, optimal control system design, and system performance analysis. Gazebo simulator provides 3D simulation of the robotic system, sensors, and control interfaces. It also enables simulation of the world environment, allowing the simulated robot to operate in a modelled environment. The model based controller for kinematic control of the non-holonomic omnidirectional platform is tested and validated through experimental results obtained from the simulated and the physical robot. The challenges of the kinematic model based controller including the mathematical and kinematic singularities are discussed and the solution to enable an optimal kinematic model based controller is presented. The kinematic singularity associated with the non-holonomic omnidirectional robots is solved using a novel fuzzy logic based approach. The proposed approach is successfully validated and tested through the simulation and experimental results. Development of a reliable localization system is aimed to enable navigation of the platform in GPS-denied environments such as orchards. For this aim, stereo visual odometry (SVO) is considered as the core of the non-GPS localization system. Challenges of SVO are introduced and the SVO accumulative drift is considered as the main challenge to overcome. SVO drift is identified in form of rotational and translational drift. Sensor fusion is employed to improve the SVO rotational drift through the integration of IMU and SVO. A novel machine learning approach is proposed to improve the SVO translational drift using Neural-Fuzzy system and RBF neural network. The machine learning system is formulated as a drift estimator for each image frame, then correction is applied at that frame to avoid the accumulation of the drift over time. The experimental results and analyses are presented to validate the effectiveness of the methodology in improving the SVO accuracy. An enhanced SVO is aimed through combination of sensor fusion and machine learning methods to improve the SVO rotational and translational drifts. Furthermore, to achieve a robust non-GPS localization system for the platform, sensor fusion of the wheel odometry and the enhanced SVO is performed to increase the accuracy of the overall system, as well as the robustness of the non-GPS localization system. The experimental results and analyses are conducted to support the methodology

Soft sensors in automotive applications

2017 - 2018In this work, design and validation techniques of two soft sensors for the estimation of the motorcycle vertical dynamic have been proposed. The aim of this work is to develop soft sensors able to predict the rear and front stroke of a motorcycle suspension. This kind of information are typically used in the control loop of semi‐active or active suspension systems. Replacing the hard sensor with a soft sensor, enable to reduce cost and improve reliability of the system. An analysis of the motorcycle physical model has been carried out to analyze the correlation existing among motorcycle vertical dynamic quantities in order to determine which of them are necessary for the development of a suspension stroke soft sensor. More in details, a first soft sensor for the rear stroke has been developed using a Nonlinear Auto‐Regressive with eXogenous inputs (NARX) neural network. A second soft sensor for the front suspension stroke velocity has been designed using two different techniques based respectively on Digital filtering and NARX neural network. As an example of application, an Instrument Fault Detection (IFD) scheme, based on the rear stroke soft sensor, has been shown. Experimental results have demonstrated the good reliability and promptness of the scheme in detecting different typologies of faults as losing calibration faults, hold‐faults, and open/short circuit faults thanks to the soft sensor developed. Finally, the scheme has been successfully implemented and tested on an ARM microcontroller, to confirm the feasibility of a real‐time implementation on actual processing units used in such context. [edited by Author]XXX cicl