0000000000236964
AUTHOR
Bernard B. Munyazikwiye
showing 10 related works from this author
Optimization of Vehicle-to-Vehicle Frontal Crash Model Based on Measured Data Using Genetic Algorithm
2017
In this paper, a mathematical model for vehicle-to-vehicle frontal crash is developed. The experimental data are taken from the National Highway Traffic Safety Administration. To model the crash scenario, the two vehicles are represented by two masses moving in opposite directions. The front structures of the vehicles are modeled by Kelvin elements, consisting of springs and dampers in parallel, and estimated as piecewise linear functions of displacements and velocities, respectively. To estimate and optimize the model parameters, a genetic algorithm approach is proposed. Finally, it is observed that the developed model can accurately reproduce the real kinematic results from the crash test…
Design of temperature control system using conventional PID and Intelligent Fuzzy Logic controller
2015
In this paper, we present the design of temperature control for industrial heat treating furnace by using Intelligent Fuzzy Logic and PID controllers. Temperature control is important in heating processes as it can disqualify materials in terms of their physical properties when not well performed. Obviously PID temperature controller is the most used in industries to control non-linear processes. Consequently, it has been found that the output response from Fuzzy Logic is very accurate in terms of overshoot and steady state error when compared to that of PID. Moreover, both temperature controllers are modeled and simulated using MATLAB software.
Mathematical Modeling and Parameters Estimation of Car Crash Using Eigensystem Realization Algorithm and Curve-Fitting Approaches
2013
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/262196 Open Access An eigensystem realization algorithm (ERA) approach for estimating the structural system matrices is proposed in this paper using the measurements of acceleration data available from the real crash test. A mathematical model that represents the real vehicle frontal crash scenario is presented. The model's structure is a double-spring-mass-damper system, whereby the front mass represents the vehicle-chassis and the rear mass represents the passenger compartment. The physical parameters of the model are estimated using cu…
Application of Genetic Algorithm on Parameter Optimization of Three Vehicle Crash Scenarios
2017
Abstract This paper focuses on the development of mathematical models for vehicle frontal crashes. The models under consideration are threefold: a vehicle into barrier, vehicle-occupant and vehicle to vehicle frontal crashes. The first model is represented as a simple spring-mass-damper and the second case consists of a double-spring-mass-damper system, whereby the front mass and the rear mass represent the vehicle chassis and the occupant, respectively. The third model consists of a collision of two vehicles represented by two masses moving in opposite directions. The springs and dampers in the models are nonlinear piecewise functions of displacements and velocities respectively. More spec…
A state-space approach to mathematical modeling and parameters identification of vehicle frontal crash
2014
In this paper a state-space estimation procedure that relies on the time-domain analysis of input and output signals is used for mathematical modeling of vehicle frontal crash. The model is a double-spring–mass–damper system, whereby the front mass and real mass represent the chassis and the passenger compartment, respectively. It is observed that the dynamic crash of the model is closer to the dynamic crash from experimental when the mass of the chassis is greater than the mass of the passenger compartment. The dynamic crash depends on pole placement and the estimated parameters. It is noted that when the poles of the model are closer to zero, the dynamic crash of the model is far from the…
Fuzzy logic approach to predict vehicle crash severity from acceleration data
2015
Vehicle crash is a complex behavior to be investigated as a challenging topic in terms of dynamical modeling. On this aim, fuzzy logic can be utilized to analyze the crash dynamics rapidly and simply. In this paper, the experimental data of the frontal crash is recorded using an accelerometer located at the centre of the gravity of the vehicle. The acceleration signal was the raw data from which the collision intensity expressed by the kinetic energy and the jerk were derived. The fuzzy logic model was then developed from the two inputs namely kinetic energy and jerk. The output variable is the crash severity expressed as the dynamic crash. The result shows that the jerk contributes much to…
A Mathematical Model for Vehicle-Occupant Frontal Crash Using Genetic Algorithm
2016
In this paper, a mathematical model for vehicle-occupant frontal crash is developed. The developed model is represented as a double-spring-mass-damper system, whereby the front mass and the rear mass represent the vehicle chassis and the occupant, respectively. The springs and dampers in the model are nonlinear piecewise functions of displacements and velocities respectively. More specifically, a genetic algorithm (GA) approach is proposed for estimating the parameters of vehicle front structure and restraint system. Finally, it is shown that the obtained model can accurately reproduce the real crash test data taken from the National Highway Traffic Safety Administration (NHTSA). The maximu…
Speed control design for a vehicle system using fuzzy logic and PID controller
2015
This paper consists of designing fuzzy and PID controllers for controlling the vehicle speed. The dynamic of the system is modeled to provide a transfer function for the plant. Fuzzy and PID controller are designed for linear model. The external disturbances such road grade is considered to stabilizing the system. Both controllers are modeled using MATLAB Simulink software. Finally, a comparative assessment of each simulated result is done based on the response characteristics.
Prediction of Vehicle Crashworthiness Parameters Using Piecewise Lumped Parameters and Finite Element Models
2018
Estimating the vehicle crashworthiness parameters experimentally is expensive and time consuming. For these reasons different modelling approaches are utilized to predict the vehicle behaviour and reduce the need for full-scale crash testing. The earlier numerical methods used for vehicle crashworthiness analysis were based on the use of lumped parameters models (LPM), a combination of masses and nonlinear springs interconnected in various configurations. Nowadays, the explicit nonlinear finite element analysis (FEA) is probably the most widely recognized modelling technique. Although informative, finite element models (FEM) of vehicle crash are expensive both in terms of man-hours put into…
Mathematical Modelling and Analysis of Vehicle Frontal Crash using Lumped Parameters Models
2020
A full-scale crash test is conventionally used for vehicle crashworthiness analysis. However, this approach is expensive and time-consuming. Vehicle crash reconstructions using different numerical modelling approaches can predict vehicle behavior and reduce the need for multiple full-scale crash tests, thus research on the crash reconstruction has received a great attention in the last few decades. Among modelling approaches, lumped parameters models (LPM) and finite element models (FEM) are commonly used in the vehicle crash reconstruction. This thesis focuses on developing and improving the LPM for vehicle frontal crash analysis. The study aims at reconstructing crash scenarios for vehicl…