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Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

ADAS (Advanced Driver Assistance System) functions can help the driver avoid accidents or mitigate their effect when they occur, and are pre-cursors to full autonomous driving (SAE defined as Level 4+). The main goal of this work is to develop a Model-Based system to actuate the Evasive Maneuver Assist (EMA) function. A typical scenario is the situation in which longitudinal Autonomous Emergency Braking (AEB) is too late and the driver has to adopt an evasive maneuver to avoid an object suddenly appearing on the road ahead. At this time, EMA can help improve the driver’s steering and braking operation in a coordinated way. The vehicle maneuverability and response performance will be enhanced when the driver is facing the collision. The function will additionally let the vehicle steer in a predetermined optimized trajectory based on a yaw rate set point and stabilize the vehicle. The EMA function is introduced with some analysis of benchmarking data.

Vehicle electrification is one of the biggest trends in the automotive industry. Without the presence of combustion engine, which is the main noise source on conventional vehicles, noise from other components becomes more perceivable; among these components, the cooling fan is one of the major noise sources, especially during battery charging. The design of cooling fan modules is usually carried out in the early stage before building prototype vehicles. Therefore, understanding the installation effects of the cooling fan on the radiated sound is essential to secure good customer satisfaction. In this study, three different measurement setups of cooling fans are carried out: free field, wall mounted, and in-vehicle measurement. Four cooling fan prototypes with different fan blade designs are used in each measurement. Correlations of these measurements are investigated through comparisons of the measurement results.

One way to reduce carbon dioxide emissions from the current heavy-duty vehicles fleet is to replace fossil fuel with renewable fuel. This can be done by blending so-called drop-in fuels into the standard diesel fuel. However, problems such as insoluble impurities may arise when the fuels are mixed. These precipitates, known as soft particles, can cause deposits in the fuel system, e.g., injectors and fuel filters, reducing the engine´s performance. The most used drop-in fuel today is biodiesel which, is blended with different concentrations. To better understand how soft particles are formed in the vehicle´s fuel system, the degradation of biodiesel blends in the engine has been investigated. This study explores biodiesel blends´ degradation process by comparing the incoming fuel with the return fuel from a modern diesel engine to investigate how the fuel is affected by this process. The engine was run using different blends of biodiesel fuel.

Renewable fuels from different feedstocks can enable sustainable transport solutions with significant reduction in greenhouse gas emissions compared to conventional petroleum-derived fuels. Nevertheless, the use of biofuels in diesel engines will still require similar exhaust gas cleaning systems as for conventional diesel. Hence, the use of diesel particulate filters (DPF) will persist as a much needed part of the vehicle’s aftertreatment system. Combustion of renewable fuels can potentially yield soot and ash with different properties as well as larger amounts of ash compared to conventional fossil fuels. The faster ash build-up and altered ash deposition pattern lead to an increase in pressure drop over the DPF, increase the fuel consumption and call for premature DPF maintenance or replacement. Prolonging the maintenance interval of the DPF for heavy-duty trucks, having a demand for high up-time, is highly desirable.

Automated Driving is revolutionizing many of the traditional ways of operation in the automotive industry. The impact on safety engineering of automotive functions is arguably one of the most important changes. There has been a need to re-think the impact of the partial or complete absence of the human driver (in terms of a supervisory entity) in not only newly developed functions but also in the qualification of the use of legacy functions in new contexts. The scope of the variety of scenarios that a vehicle may encounter even within a constrained Operational Design Domain, and the highly dynamic nature of Automated Driving, mean that new methods such as simulation can greatly aid the process of safety engineering.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.

Higher compression ratio and turbocharging, with engine downsizing can enable significant gains in fuel economy but require engine operating conditions that cause engine knock under high load. Engine knock can be avoided by supplying higher-octane fuel under such high load conditions. This study builds on previous MIT papers investigating Octane-On-Demand (OOD) to enable a higher efficiency, higher-boost higher compression-ratio engine. The high-octane fuel for OOD can be obtained through On-Board-Separation (OBS) of alcohol blended gasoline. Fuel from the primary fuel tank filled with commercially available gasoline that contains 10% by volume ethanol (E10) is separated by an organic membrane pervaporation process that produces a 30 to 90% ethanol fuel blend for use when high octane is needed. In addition to previous work, this paper combines modeling of the OBS system with passenger car and medium-duty truck fuel consumption and octane requirements for various driving cycles.

Ground impact caused by road debris can result in very severe fire accident of Electric Vehicles (EV). In order to study the ground impact accidents, a Finite Element model of the battery pack structure is carefully set up according to the practical designs of EVs. Based on this model, the sequence of the deformation process is studied, and the contribution of each component is clarified. Subsequently, four designs, including three enhanced shield plates and one enhanced housing box, are investigated. Results show that the BRAS (Blast Resistant Adaptive Sandwich) shield plate is the most effective structure to decrease the deformation of the battery cells. Compared with the baseline case, which adopts a 6.35-mm-thick aluminum sheet as the shield plate, the BRAS can reduce the shortening of cells by more than 50%. Another type of sandwich structure, the NavTruss, can also improve the safety of battery pack, but not as effectively as the BRAS.

With the advent of ISO 26262 there is an increased emphasis on top-down design in the automotive industry. While the standard delivers a best practice framework and a reference safety lifecycle, it lacks detailed requirements for its various constituent phases. The lack of guidance becomes especially evident for the reuse of legacy components and subsystems, the most common scenario in the cost-sensitive automotive domain, leaving vehicle architects and safety engineers to rely on experience without methodological support for their decisions. This poses particular challenges in the industry which is currently undergoing many significant changes due to new features like connectivity, servitization, electrification and automation. In this paper we focus on automated driving where multiple subsystems, both new and legacy, need to coordinate to realize a safety-critical function.

The effect of blockage due to the presence of the wind tunnel walls has been known since the early days of wind tunnel testing. Today there are several blockage correction methods available for correcting the measured aerodynamic drag. Due to the shape of the test object, test conditions and wind tunnel dimensions the effect on the flow may be different for two cab variants. This will result in a difference in the drag delta between so-called open-road conditions and the wind tunnel. This makes it more difficult to evaluate the performance of two different test objects when they are both tested in a wind tunnel and simulated in CFD. A numerical study where two different cab shapes were compared in both open road condition, and in a digital wind tunnel environment was performed.

MIT Lincoln Laboratory is tasked by the U.S. Federal Aviation Administration to investigate the use of the NEXRAD polarimetric radars* for the remote sensing of icing conditions hazardous to aircraft. A critical aspect of the investigation concerns validation that has relied upon commercial airline icing pilot reports and a dedicated campaign of in situ flights in winter storms. During the month of February in 2012 and 2013, the Convair-580 aircraft operated by the National Research Council of Canada was used for in situ validation of snowstorm characteristics under simultaneous observation by NEXRAD radars in Cleveland, Ohio and Buffalo, New York. The most anisotropic and easily distinguished winter targets to dual pol radar are ice crystals.

The after treatment devices (ATD) used in internal combustion engine (IC-engine) exhaust systems are mainly designed with emphasis on emission control, i.e. chemical efficiency, while paying less attention to the acoustic performance. In automotive applications, the duct diameters are so small that studying the acoustic wave propagation only in the plane wave frequency range is usually sufficient. In the case of medium speed IC-engines, used for example in power plants and ships, the three dimensional acoustic phenomena must also be taken into account. The main elements of the medium speed IC-engine ATD are the selective catalytic reducer (SCR) and oxidation catalyst (OC), which are based on a large amount of coated channels, i.e. the substrates. The number and type of the substrates depends not only on the regional environment legislations but also on the engine type.

Regulations stipulating the design of motorcycle silencers are strict, especially when the unit incorporates fibrous absorbing materials. Therefore, innovative designs substituting such materials while still preserving acceptable level of characteristic sound are currently of interest. Micro perforated elements are innovative acoustic solutions, which silencing effect is based on the dissipation of the acoustic wave energy in a pattern of sub-millimeter apertures. Similarly to fibrous materials the micro-perforated materials have been proved to provide effective sound absorption in a wide frequency range. Additionally, the silencer is designed as a two-stage system that provides an optimal solution for a variety of exploitation conditions. In this paper a novel design for a cruiser type motorcycle silencer, based on micro-perforated elements, is presented.

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.

The use of innovative power sources in future cars has long-ranging implications on vehicle safety. We studied these implications in the context of the guidance on software tool qualification in the then current ISO 26262 draft, when building an urban concept vehicle to participate in the 2011 Shell Eco-Marathon. While the guidance on tool qualification is detailed, the guidance in regard to tools integrated into tool chains is limited. It only points out that the environment that tools execute in needs to be taken into consideration. In this paper we clarify the implications of tool chains on tool qualification in the context of ISO 26262 by focusing on answering two questions; first, are there parts of the development environment related to tool integration that are likely to fall outside of tool qualification efforts as currently defined by ISO 26262; secondly, can we define if, and -if so- how, tool integration is affected by ensuring functional safety.

The fuel energy consumption of subsonic air transportation is examined. The focus is on identification and quantification of fundamental engineering design tradeoffs which drive the design of subsonic tube and wing transport aircraft. The sensitivities of energy efficiency to recent and forecast technology developments are also examined.

Battery packs for Hybrids, Plug-in Hybrids, and Electric Vehicles are assembled from a system of modules (sheets) with a tight sheet metal casing around them. Each module consists of an array of individual cells which vary in the composition of electrodes and separator from one manufacturer to another. In this paper a general procedure is outlined on the development of a constitutive and computational model of a cylindrical cell. Particular emphasis is placed on correct prediction of initiation and propagation of a tearing fracture of the steel can. The computational model correctly predicts rupture of the steel can which could release aggressive chemicals, fumes, or spread the ignited fire to the neighboring cells. The initiation site of skin fracture depends on many factors such as the ductility of the casing material, constitutive behavior of the system of electrodes, and type of loading.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.