Search Results

Abstract This article proposes a novel approach of a hybrid system of physics and data-driven modeling for accurately estimating the state of charge (SOC) of a battery. State of Charge (SOC) is a measure of the remaining battery capacity and plays a significant role in various vehicle applications like charger control and driving range predictions. Hence the accuracy of the SOC is a major area of interest in the automotive sector. The method proposed in this work takes the state-of-the-art practice of Kalman filter (KF) and merges it with intelligent capabilities of machine learning using neural networks (NNs). The proposed hybrid system comprises a physics-based battery model and a plurality of NNs eliminating the need for the conventional KF while retaining its features of the predictor-corrector mechanism of the variables to reduce the errors in estimation.

Abstract The 2010 Environmental Protection Agency (EPA) Emission Standard for heavy-duty engines required 0.2 g/bhp-hr over certification cycles (cold and hot Federal Test Procedure [FTP]), and the California Air Resources Board (CARB) standards require 0.02 g/bhp-hr for the same cycles leading to a 90% reduction of overall oxides of nitrogen (NOx) emissions. Similar reductions may be considered by the EPA through its Cleaner Trucks Initiative program. In this article, aftertreatment system components consisting of a diesel oxidation catalyst (DOC); a selective catalytic reduction (SCR) catalyst on a diesel particulate filter (DPF), or SCR-F; a second DOC (DOC2); and a SCR along with two urea injectors have been analyzed, which could be part of an aftertreatment system that can achieve the 0.02 g/bhp-hr standard.

Abstract Numerous researchers are committed to finding solutions to the path planning problem of intelligence-based vehicles. How to select the appropriate algorithm for path planning has always been the topic of scholars. To analyze the advantages of existing path planning algorithms, the intelligence-based vehicle path planning algorithms are classified into conventional path planning methods, intelligent path planning methods, and reinforcement learning (RL) path planning methods. The currently popular RL path planning techniques are classified into two categories: model based and model free, which are more suitable for complex unknown environments. Model-based learning contains a policy iterative method and value iterative method. Model-free learning contains a time-difference algorithm, Q-learning algorithm, state-action-reward-state-action (SARSA) algorithm, and Monte Carlo (MC) algorithm.

Abstract The advancement in vision sensors and embedded technology created the opportunity in autonomous vehicles to look ahead in the future to avoid potential obstacles and steep regions to reach the target location as soon as possible and yet maintain vehicle safety from rollover. The present work focuses on developing a nonlinear model predictive controller (NMPC) for a high-speed off-road autonomous vehicle, which avoids undesirable conditions including stationary obstacles, moving obstacles, and steep regions while maintaining the vehicle safety from rollover. The NMPC controller is developed using CasADi tools in the MATLAB environment. The CasADi tool provides a platform to formulate the NMPC problem using symbolic expressions, which is an easy and efficient way of solving the optimization problem. In the present work, the vehicle lateral dynamics are modeled using the Pacejka nonlinear tire model.

Abstract The increased scope of active and passive safety in motor vehicles and the enforcement of approval requirements for individual parts and assemblies affect the design and parameters of a car’s motion. The tire, which transmits forces and torques onto the road’s surface is a particularly crucial element in the vehicle. Its structure, type of mixture, and operating conditions determine the safety of vehicle motion. The three-axial force system loads the tires of the car and affects both the tread and sidewall, as well as the suspension and steering system. Taking into account the controllability and stability of movement, the tire is subjected to dynamic and thermal loads, as well as to wear and random damage. This negatively impacts on the joints of composite layers. The sudden loss of pressure in the tire can lead to serious accidents, especially when moving at high speeds, due to changes in the rolling radius.

Abstract In-phase rear-wheel steering, where rear wheels are steered in the same direction of front wheels, has been widely investigated in the literature for vehicle stability improvements along with stability control systems. Much faster response can be achieved by steering the rear wheels automatically during an obstacle avoidance maneuver without applying the brakes where safe stopping distance is not available. Sudden lane change movements still remain challenging for heavy articulated vehicles, such as tractor and semitrailer combinations, particularly on roads with low coefficient of adhesion. Different lateral accelerations acting on tractor and semi-trailer may cause loss of stability resulting in jackknifing, trailer-swing, rollover, or slip-off. Several attempts have been made in the literature to use active steering of semi-trailer’s rear wheels to prevent jackknifing and rollover.

Abstract Unstable articulated vehicles pose a serious threat to the occupants driving them as well as the occupants of the vehicles around them. Articulated vehicles typically experience three types of instability: snaking, jack-knifing, and rollover. An articulated vehicle subjected to any of these instabilities can result in major accidents. In this study a Nonlinear Model Predictive Control (NMPC) that applies brake-based torque vectoring on the trailer is developed to improve the articulated vehicle stability. The NMPC formulation includes tire saturation and applies constraints to prevent rollover. The controller output is a left and right brake force allowing the longitudinal velocity change to be incorporated into the model. Simulations were conducted to instigate snaking and jack-knifing and show the NMPC controller result compared to a simple proportional controller.

Abstract Excessive brake heating of trucks on downgrades is a cause of continuing concern for the Wyoming Department of Transportation (WYDOT). Brake failure on downgrades characteristically takes a catastrophic toll on lives and property. The Grade Severity Rating System (GSRS) developed by the Federal Highway Administration (FHWA) recommends a maximum safe speed limit that has been identified as a feasible remedy for reducing the incidence of downgrade truck crashes. However, truck characteristics and roadway geometrics have changed over the years following the development of the GSRS. To deal with this development, a research project was initiated by the WYDOT in 2016 to update the GSRS model. The test truck used for the field tests in the prior research project was fitted with disc brakes on the front axle and drum brakes on the rear axle. However, disc brakes represent only about 20% of the brake market.

Abstract Particulate Matter (PM) is one of the most sought-after exhaust emissions from Heavy-Duty Diesel Engines (HDDEs) to reduce. Several regulations in Europe and North America have led the way in drastically reducing PM of both on-road and off-road engines through stringent adoption of Diesel Particulate Filters (DPFs) and advanced combustion techniques. The effects of these advanced aftertreatment systems were studied using standardized testing procedures and equipment. While PM is defined as a “single” criteria pollutant, its complex structure entails several chemical compounds and molecules, displaying a whole spectrum of particle sizes. In addition, the morphology of some volatile compounds is shown to be affected by the interaction with background air during exhaust dilution and cooling.

Abstract This study proposes a method for the rapid detection and location of cavity defects in ballastless track structures of high-speed railways in service. First, the propagation law of air-coupled ultrasonic Lamb waves in the ballastless track structure is studied. Theoretical calculation results show that the ultrasonic Lamb wave group velocity of the A2 mode in the track plate is 4000 m/s. Then, the excitation and reception methods of the air-coupled ultrasound are studied. Theoretical and experimental results show that the A2 mode Lamb wave can be generated by the 3.8° oblique incidence of the ballastless track structure. Finally, an experimental system for air-coupled ultrasonic testing is constructed. A pair of air-coupled ultrasonic probes is used to provide excitation and reception Lamb wave signals at an inclined angle of 3.8°, 20 mm away from the surface of the track plate, and 40 mm/step along the scanning direction.

Abstract Vehicle rolling resistance and weight are two of the factors that affect fuel economy. The vehicle tire rolling resistance has a more significant influence than aerodynamics drags on fuel economy at lower vehicle speeds, particularly true for medium- and heavy-duty trucks. Less vehicle weight reduces inertia loads, uphill grade resistance, and rolling resistance. The influence of weight on the fuel economy can be considerable particularly in light- to medium-duty truck classes because the weight makes up a larger portion of gross vehicle weight. This article presents an empirical investigation and a numerical analysis of the influences of rolling resistance and weight on the fuel economy of medium-duty trucks. The experimental tests include various tires and payloads applied on a total of 21vehicle configurations over three road profiles. These tests are used to assess the sensitivity of rolling resistance and weight to the vehicle fuel economy.

Abstract Fuel economy is a crucial parameter in long-haulage heavy-duty vehicles. Researchers tended to focus initially on engine combustion efficiency, while modern researchers turn their attention to the energy consumption of engine accessories in an attempt to enhance fuel economy. The accessories investigated in this study include the cooling fan, water pump, air compressor, power steering pump, air-conditioning (AC) compressor, and generator. Normally, accessory energy consumption analysis is based on rig data and simulation results. Here, we focus on the disparate test environments between the rig and vehicle to establish a novel steady power test method; the proposed method provides accurate accessory power data under different working conditions. A typical highway driving cycle is selected to collect accessory duty-cycle. The heavy-duty vehicle accessories’ energy consumption distribution under highway road conditions is obtained through the repeated road tests.

Abstract Emissions from motor vehicles are generally recognized to pollute the outside air, with negative effects on human health and the environment. Little is known about the extent to which these pollutants enter the interior of the vehicles through their ventilation systems. The cabin air quality inside vehicles is very lightly regulated around the world, and there is no recognized standard method for measuring pollution ingress. This article tests the effectiveness of a method originally proposed in an SAE paper in 2019 for characterizing the degree of particle ingress. This cabin air quality index is hypothesized to give a repeatable, characteristic value for the vehicle to reduce in-cabin pollutant concentration compared to outside pollutant concentration, which may be suitable for inter-vehicle comparison.

Abstract Certain advanced driver assistance systems (ADAS) have the potential to boost energy efficiency in real-world scenarios. This article details a radar-based driver assistance scheme designed to minimize fuel consumption for a commercial vehicle by predictively optimizing braking and driving torque inputs while accommodating the driver’s demand. The workings of the proposed scheme are then assessed with a novel integration of the driver assistance functionality in randomized traffic microsimulation. Although standardized test procedures are intended to mimic urban and highway speed profiles for the purposes of evaluating fuel economy and emissions, they do not explicitly consider the interactions present in real-world driving between the ego vehicle equipped with ADAS and other vehicles in traffic. This article presents one approach to address the drawback of standardized test procedures for evaluating the fuel economy benefits of ADAS technologies.

Abstract The rapid utilization of fossil fuels has triggered the finding of alternative renewable fuel that replaces or reduces the consumption by alternative fuels for fueling compression ignition (CI) engines. One such renewable fuel is ethanol which can be manufactured from biomass. The present study details the utilization of an optimum amount of ethanol in CI engine by modifying the operating parameters. It was already published in the previous paper that 45% ethanol can be utilized along with diesel using 10% butanol as cosolvent. This fuel is also meeting the minimum requirement with respect to properties as per ASTM standards. This experimental study was performed to investigate the influence of modifying the engine operating parameters on the performance, combustion, and emission parameters fueled with the blend containing 45% ethanol under various load conditions.

Abstract Rubber elements present highly nonlinear mechanical properties affected by frequency and amplitude of excitation, prestrain and temperature, etc. Finite element (FE) models and lumped parameter models can be distinguished in the development of constitutive models of rubbers. Based on the concept of overlay model, different kinds of viscoelastic, or frequency-dependent models, and elastoplastic/friction, or amplitude-dependent models, are compared in terms of their modelling approach, parameters identification process and applications. Prestrain-dependent models and temperature-dependent thermo-mechanical models are also reviewed, including some special models which are not based on the concept of the overlay model. Experimental and computational studies of cylindrical bushings subjected to coupled deformation modes are analyzed and discussed.

Abstract The article presents results of tests performed with the use of a ship engine of the type Sulzer 6AL20/24. The goal of the tests was to create and verify an identification procedure for the analyzed object’s reliability states to be used without interfering with the object operation processes. The proposed method is based on an analysis of vibrations and noise generated during the engine operation, which are considered to be the most significant diagnostic signals. The signals of the engine vibrations and noise recorded during the engine operation on a laboratory test stand have been analyzed in the time domain. A number of the recorded signal characteristics are calculated. The characteristics are statistically analyzed in order to choose those which can provide the basis for the identification of reliability states. Next, based on the spaces of ability and inability, states are formulated.

Abstract Heavy-duty (HD) engines for sale in the United States must be demonstrated to emit below allowable criteria and particulate emission limits over the operational load and speed cycle specified by the Federal Test Procedure (FTP) Heavy-Duty certification test. The inherently nonlinear load response of internal combustion engines tends to increase torque variability during the most dynamic portions of the test cycle. This clouds assessment of engine developments intended to improve transient performance and leads to frequent invalidation of certification tests. This work sought to develop and evaluate test torque control strategies that reduce this variability. Several load-control algorithms were evaluated for this purpose using a Cummins ISX15 HD diesel engine loaded with a transient alternating current (AC) dynamometer.

Abstract Letter from the Special Issue Editors

Abstract In modern diesel fuel a proportion of biodiesel is blended with petro-diesel to reduce environmental impacts. However, it can adversely affect the operation of nonwoven coalescing filter media when separating emulsified water from diesel fuel. This can be due to factors such as increasing water content in the fuel, a reduction in interfacial tension (IFT) between the water and diesel, the formation of more stable emulsions, and the generation of smaller water droplets. Standard water/diesel separation test methods such as SAE J1488 and ISO 16332 use monoolein, a universal surface-active agent, to simulate the effects of biodiesel on the fuel properties as part of water separation efficiency studies. However, the extent to which diesel/monoolein and diesel/biodiesel blends are comparable needs to be elucidated if the underlying mechanisms affecting coalescence of very small water droplets in diesel fuel with a low IFT are to be understood.