Influence of driving style on fuel consumption and Emissions in diesel-powered passenger car

This paper presents the main results of a study on the influence of driving style on fuel consumption and pollutant emissions of diesel passenger car in urban traffic. Driving styles (eco, normal or aggressive) patterns were based on the “eco-driving” criteria. The methodology is based on on-board emission measurements in real urban traffic in the city of Madrid. Five diesel passenger cars, have been tested. Through a statistical analysis, a Dynamic Performance Index was defined for diesel passenger cars. Likewise, the CO, NOX and HC emissions were compared for each driving style for the tested vehicles. Eco-driving reduces by 14% fuel consumption and CO2 emissions, but aggressive driving increase consumption by 40%. Aggressive driving increases NOX emission by more than 40%. CO and HC, show different trends, but being increased in eco-driving style.

Proposal of a dynamic performance index to analyze driving pattern effect on car emissions

The contributions of driver behaviour as well as surrounding infrastructure are decisive on pollutant emissions from vehicles in real traffic situations. This article deals with the preliminary study of the interaction between the dynamic variables recorded in a vehicle (driving pattern) and pollutant emissions produced over a given urban route. It has been established a “dynamic performance index”-DPI, which is calculated from some driving pattern parameters, which in turn depends on traffic congestion level and route characteristics, in order to determine whether the driving has been aggressive, normal or calm. Two passenger cars instrumented with a portable activity measurement system -to record dynamic variables- and on-board emission measurement equipment have been used. This study has shown that smooth driving patterns can reduce up to 80% NOX emissions and up to 20% of fuel in the same route

Driving assistance system applied in curves for real vehicles | Sistema de ayuda a la conducción en curvas para vehículos reales

Decreasing the accidents on highway and urban environments is the main motivation for the research and developing of driving assistance systems, also called ADAS (Advanced Driver Assistance Systems). In recent years, there are many applications of these systems in commercial vehicles: ABS systems, Cruise Control (CC), parking assistance and warning systems (including GPS), among others. However, the implementation of driving assistance systems on the steering wheel is more limited, because of their complexity and sensitivity. This paper is focused in the development, test and implementation of a driver assistance system for controlling the steering wheel in curve zones. This system is divided in two levels: an inner control loop which permits to execute the position and speed target, softening the action over the steering wheel, and a second control outer loop (controlling for fuzzy logic) that sends the reference to the inner loop according the environment and vehicle conditions. The tests have been done in different curves and speeds. The system has been proved in a commercial vehicle with satisfactory results.

Ultrasonic sensors in urban traffic driving-aid systems

Currently, vehicles are often equipped with active safety systems to reduce the risk of accidents, most of which occur in urban environments. The most prominent include Antilock Braking Systems (ABS), Traction Control and Stability Control. All these systems use different kinds of sensors to constantly monitor the conditions of the vehicle, and act in an emergency. In this paper the use of ultrasonic sensors in active safety systems for urban traffic is proposed, and the advantages and disadvantages when compared to other sensors are discussed. Adaptive Cruise Control (ACC) for urban traffic based on ultrasounds is presented as an application example. The proposed system has been implemented in a fully-automated prototype vehicle and has been tested under real traffic conditions. The results confirm the good performance of ultrasonic sensors in these systems. ©2011 by the authors.

Traffic jam driving with NMV avoidance

n recent years, the development of advanced driver assistance systems (ADAS) – mainly based on lidar and cameras – has considerably improved the safety of driving in urban environments. These systems provide warning signals for the driver in the case that any unexpected traffic circumstance is detected. The next step is to develop systems capable not only of warning the driver but also of taking over control of the car to avoid a potential collision. In the present communication, a system capable of autonomously avoiding collisions in traffic jam situations is presented. First, a perception system was developed for urban situations—in which not only vehicles have to be considered, but also pedestrians and other non-motor-vehicles (NMV). It comprises a differential global positioning system (DGPS) and wireless communication for vehicle detection, and an ultrasound sensor for NMV detection. Then, the vehicle's actuators – brake and throttle pedals – were modified to permit autonomous control. Finally, a fuzzy logic controller was implemented capable of analyzing the information provided by the perception system and of sending control commands to the vehicle's actuators so as to avoid accidents. The feasibility of the integrated system was tested by mounting it in a commercial vehicle, with the results being encouraging.

Non-periodic driving of coupled oscillators:a spherical swing

Nonlinearly coupled, damped oscillators at 1:1 frequency ratio, one oscillator being driven coherently for efficient excitation, are exemplified by a spherical swing with some phase-mismatch between drive and response. For certain damping range, excitation is found to succeed if it lags behind, but to produce a chaotic attractor if it leads the response. Although a period-doubhng sequence, for damping increasing, leads to the attractor, this is actually born as a hard (as regards amplitude) bifurcation at a zero growth-rate parametric line; as damping decreases, an unstable fixed point crosses an invariant plane to enter as saddle-focus a phase-space domain of physical solutions. A second hard bifurcation occurs at the zero mismatch line, the saddle-focus leaving that domain. Times on the attractor diverge when approaching either fine, leading to exactly one-dimensional and noninvertible limit maps, which are analytically determined.

Using floating car data to analyse the effects of ITS measures and eco-driving

The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied.

Factors driving the carbon mineralization priming effect in a sandy loam soil amended with different types of biochar

The effect of biochar on the soil carbon mineral- ization priming effect depends on the characteristics of the raw materials, production method and pyrolysis conditions. The goal of the present study is to evaluate the impact of three different types of biochar on physicochemical properties and CO2 emissions of a sandy loam soil. For this purpose, soil was amended with three different biochars (BI, BII and BIII) at a rate of 8 wt % and soil CO2 emissions were measured for 45 days. BI is produced from a mixed wood sieving from wood chip production, BII from a mixture of paper sludge and wheat husks and BIII from sewage sludge. Cumulative CO2 emissions of biochars, soil and amended soil were well fit to a simple first-order kinetic model with correlation coef- ficients (r 2 ) greater than 0.97. Results show a negative prim- ing effect in the soil after addition of BI and a positive prim- ing effect in the case of soil amended with BII and BIII. These results can be related to different biochar properties such as carbon content, carbon aromaticity, volatile matter, fixed carbon, easily oxidized organic carbon or metal and phenolic substance content in addition to surface biochar properties. Three biochars increased the values of soil field capacity and wilting point, while effects over pH and cation exchange capacity were not observed.

Co-simulation Methodologies for Hybrid and Electric Vehicle Dynamics

In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.

Understanding how to reduce road transport emissions : modelling the impact of eco-driving

Entre los problemas medioambientales más trascendentales para la sociedad, se encuentra el del cambio climático así como el de la calidad del aire en nuestras áreas metropolitanas. El transporte por carretera es uno de los principales causantes, y como tal, las administraciones públicas se enfrentan a estos problemas desde varios ángulos: Cambios a modos de transporte más limpios, nuevas tecnologías y combustibles en los vehículos, gestión de la demanda y el uso de tecnologías de la información y la comunicación (ICT) aplicadas al transporte. En esta tesis doctoral se plantea como primer objetivo el profundizar en la comprensión de cómo ciertas medidas ICT afectan al tráfico, las emisiones y la propia dinámica de los vehículos. El estudio se basa en una campaña de recogida de datos con vehículos flotantes para evaluar los impactos de cuatro medidas concretas: Control de velocidad por tramo, límites variables de velocidad, limitador de velocidad (control de crucero) y conducción eficiente (eco‐driving). Como segundo objetivo, el estudio se centra en la conducción eficiente, ya que es una de las medidas que más ahorros de combustible presenta a nivel individual. Aunque estas reducciones están suficientemente documentadas en la literatura, muy pocos estudios se centran en estudiar el efecto que los conductores eficientes pueden tener en el flujo de tráfico, y cuál sería el impacto si se fuera aumentando el porcentaje de este tipo de conductores. A través de una herramienta de microsimulación de tráfico, se han construido cuatro modelos de vías urbanas que se corresponden con una autopista urbana, una arteria, un colector y una vía local. Gracias a los datos recogidos en la campaña de vehículos flotantes, se ha calibrado el modelo, tanto el escenario base como el ajuste de parámetros de conducción para simular la conducción eficiente. En total se han simulado 72 escenarios, variando el tipo de vía, la demanda de tráfico y el porcentaje de conductores eficientes. A continuación se han calculado las emisiones de CO2 and NOx mediante un modelo de emisiones a nivel microscópico. Los resultados muestran que en escenarios con alto porcentaje de conductores eficientes y altas demandas de tráfico las emisiones aumentan. Esto se debe a que las mayores distancias de seguridad y las aceleraciones y frenadas suaves hacen que aumente la congestión, produciendo así mayores emisiones a nivel global. Climate change and the reduced air quality in our metropolitan areas are two of the main environmental problems that the society is addressing currently. Being road transportation one of the main contributors, public administrations are facing these problems from different points of view: shift to cleaner modes, new fuels and vehicle technologies, demand management and the use of information and communication technologies (ICT) applied to transportation. The first objective of this thesis is to understand how certain ICT measures affect traffic, emissions and vehicle dynamics. The study is based on a data collection campaign with floating vehicles to evaluate the impact of four specific measures: section speed control, variable speed limits, cruise control and eco‐driving. The second objective of the study focuses on eco‐driving, as it is one of the measures that present the largest fuel savings at an individual level. Although these savings are well documented in the literature, few studies focus on how ecodrivers affect the surrounding vehicles and the traffic, and what would be the impact in case of different eco‐drivers percentage. Using a traffic micro‐simulation tool, four models in urban context have been built, corresponding to urban motorway, urban arterial, urban collector and a local street. Both the base‐case and the parameters setting to simulate eco‐driving have been calibrated with the data collected through floating vehicles. In total 72 scenarios were simulated, varying the type of road, traffic demand and the percentage of eco‐drivers. Then, the CO2 and NOx emissions have been estimated through the use of an emission model at microscopic level. The results show that in scenarios with high percentage of co‐drivers and high traffic demand the emissions rise. Higher headways and smooth acceleration and decelerations increase congestion, producing higher emissions globally.