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Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

This paper details the advancements and outcomes of the NEXTCAR (Next-Generation Energy Technologies for Connected and Automated on-Road Vehicles) program, an initiative led by the Advanced Research Projects Agency-Energy (ARPA-E). The program focusses on harnessing the full potential of Connected and Automated Vehicle (CAV) technologies to develop advanced vehicle dynamic and powertrain control technologies (VD&PT). These technologies have shown the capability to reduce energy consumption by 20% in conventional and hybrid electric cars and trucks at automation levels L1-L3 and by 30% L4 fully autonomous vehicles. Such reductions could lead to significant energy savings across the entire U.S. vehicle fleet.

To better understand the technical challenges of commercial vehicle electrification, BorgWarner converted a production Internal Combustion Engine (ICE) medium duty truck into a fully electrified vehicle. The resulting vehicle includes a newly developed dual-motor rear Beam eAxle driven by a pair of high-performance silicon carbide (SiC) inverters, an 800V battery system, and a new thermal management system customized for the electric vehicle. This paper will detail the conversion process along with the key components involved in the build. The resulting performance of the fully electrified commercial vehicle will be presented in comparison to the original production vehicle. The primary aim is to outline what is entailed in an electric vehicle conversion and to share the learnings gained throughout this build and development process.

The transition towards electrification in commercial vehicles has received more attention in recent years. This paper details the conversion of a production Medium-Duty class-5 commercial truck, originally equipped with a gasoline engine and 10-speed automatic transmission, into a battery electric vehicle (BEV). The conversion process involved the removal of the internal combustion engine, transmission, and differential unit, followed by the integration of an ePropulsion system, including a newly developed dual-motor beam axle that propels the rear wheels. Other systems added include an 800V/99 kWh battery pack, advanced silicon carbide (SiC) inverters, an upgraded thermal management system, and a DC fast charging system. A key part of the work was the development of the propulsion system controls, which prioritized drivability, NVH suppression, and energy optimization.

Emissions and fuel economy certification testing for vehicles is carried out on a chassis dynamometer using standard test procedures. The vehicle coastdown method (SAE J2263) used to experimentally measure the road load of a vehicle for certification testing is a time-consuming procedure considering the high number of distinct variants of a vehicle family produced by an automaker today. Moreover, test-to-test repeatability is compromised by environmental conditions: wind, pressure, temperature, track surface condition, etc., while vehicle shape, driveline type, transmission type, etc. are some factors that lead to vehicle-to-vehicle variation. Controlled lab tests are employed to determine individual road load components: tire rolling resistance (SAE J2452), aerodynamic drag (wind tunnels), and driveline parasitic loss (dynamometer in a driveline friction measurement lab). These individual components are added to obtain a road load model to be applied on a chassis dynamometer.

To accurately evaluate the energy consumption benefits provided by connected and automated vehicles (CAV), it is necessary to establish a reasonable baseline virtual driver, against which the improvements are quantified before field testing. Virtual driver models have been developed that mimic the real-world driver, predicting a longitudinal vehicle speed profile based on the route information and the presence of a lead vehicle. The Intelligent Driver Model (IDM) is a well-known virtual driver model which is also used in the microscopic traffic simulator, SUMO. The Enhanced Driver Model (EDM) has emerged as a notable improvement of the IDM. The EDM has been shown to accurately forecast the driver response of a passenger vehicle to urban and highway driving conditions, including the special case of approaching a signalized intersection with varying signal phases and timing. However, most of the efforts in the literature to calibrate driver models have focused on passenger vehicles.

Super Truck II is a 48V mild hybrid class 8 truck with an all auxiliary loads powered purely by the battery pack. Electric Heating Ventilation and Air Conditioning (HVAC) load is the most prominent battery load during the hotel period, when the truck driver is resting inside the sleeper. For the PACCAR Super Truck II (ST-II) project a 48 V battery system provides the required power during the hotel period. A cabin-HVAC model estimates the electric load on the 48V battery system, allowing the control system to implement an efficient energy management strategy that avoids engine idling during the hotel period. The thermal model accounts for the sun load due to the time of day and the geographic location of the truck during the hotel period. The cabin-HVAC model has two parts. First, a grey box model with two heat exchangers (Condenser and Evaporator) working in unison with refrigerant mass flow rate as an input and HVAC load as an output.

Gear profile deviation is the difference in gear tooth profile from the ideal involute geometry. There are many causes that result in the deviation. Deflection under load, manufacturing, and thermal effects are some of the well-known causes that have been reported to cause deviation of the gear tooth profile. The profile deviation caused by gear tooth profile deformation due to interference-fit assembly has not been discussed previously. Engine timing gear trains, transmission gearboxes, and wind turbine gearboxes are known to use interference-fit to attach the gear to the rotating shaft. This paper discusses the interference-fit joint design and the mechanism of tooth profile deformation due to the interference-fit assembly in gear trains. A new analytical method to calculate the profile slope deviation change due to interference-assembly of parallel axis spur gears is presented.

The ported shroud casing treatment for turbocharger compressors offers a wider operating flow range, elevated boost pressures at low compressor mass flow rates, and reduced broadband whoosh noise in spark-ignition internal combustion engine applications. However, the casing treatment elevates tonal noise at the blade-pass frequency (BPF). Typical rotational speeds of compressors employed in practice push BPF noise to high frequencies, which then promote multi-dimensional acoustic wave propagation within the compressor ducting. As a result, in-duct acoustic measurements become sensitive to the angular location of pressure transducers on the duct wall. The present work utilizes a steady-flow turbocharger gas stand featuring a unique rotating compressor inlet duct to quantify the variation of noise measured around the duct at different angular positions.

Having connectivity among ground vehicles brings about benefits in fuel economy improvement, traffic mobility enhancement and undesired emission reductions. On the other hand, Unmanned Aerial Vehicles (UAV) have proven to help in getting aerial data to end users in an affordable manner. When UAVs are equipped with cameras, they can get information about the terrain they are flying over. Moreover, using Vehicle-to-Everything (V2X) communication technologies, it is possible to form a communication link between UAVs and the connected ground vehicle networks comprising of Connected and Autonomous vehicles (CAVs). To investigate and exploit the potential benefits and use cases of a broad vehicle network, a microscopic traffic simulator modified previously by our group with the addition of nearby UAVs is used to integrate simulated Connected UAVs flying above a realistic simulation of heterogeneous traffic flow containing both CAVs and non-CAVs.

A key enabler to maximizing the benefits from advanced powertrain technologies is to adopt a systems integration approach and develop optimized controls that consider the propulsion system and vehicle as a whole. This approach becomes essential when incorporating Advanced Driver Assistance Systems (ADAS) and communication technologies, which can provide information on future driving conditions. This may enable the powertrain control system to further improve the vehicle performance and energy efficiency, shifting from an instantaneous optimization of energy consumption to a predictive and “look-ahead” optimization. Benefits from this approach can be realized at all levels of electrification, from conventional combustion engines to hybrid propulsion systems and full electric vehicles, and at all levels of vehicle automation.

There are many methods developed over the past decade to solve the problem of energy management control for hybrid electric vehicles. A novel method is introduced in this paper to address the same problem which reduces the problem to a set of physical equations and maps. In simple terms, this method directly calculates the actual cost or savings in fuel energy from the generation or usage of electric energy. It also calculates the local optimum electric power that yields higher electric fuel savings (EFS) or lower electric fuel cost (EFC) in the fuel energy that is spent for driving the vehicle (which in general does not take the system to the lowest engine Brake Specific Fuel Consumption (BSFC)). Based on this approach, a control algorithm is developed which attempts to approach the global optimum over a drive cycle.

The platooning of connected automated vehicles (CAV) possesses the significant potential of reducing energy consumption in the Intelligent Transportation System (ITS). Moreover, with the rapid development of eco-driving technology, vehicle platooning can further enhance the fuel efficiency by optimizing the efficiency of the powertrain. Since road grade is a main factor that affects the energy consumption of a vehicle, the estimation of the road grade with high accuracy is the key factor for a connected vehicle platoon to optimize energy consumption using vehicle-to-vehicle (V2V) communication. Commonly, the road grade is quantified by single consumer grade global positioning system (GPS) with the geodetic height data which is rough and in the meter-level, increasing the difficulty of precisely estimating the road grade.

The assessment of fuel economy of new vehicles is typically based on regulatory driving cycles, measured in an emissions lab. Although the regulations built around these standardized cycles have strongly contributed to improved fuel efficiency, they are unable to cover the envelope of operating and environmental conditions the vehicle will be subject to when driving in the “real-world”. This discrepancy becomes even more dramatic with the introduction of Connectivity and Automation, which allows for information on future route and traffic conditions to be available to the vehicle and powertrain control system. Furthermore, the huge variability of external conditions, such as vehicle load or driver behavior, can significantly affect the fuel economy on a given route. Such variability poses significant challenges when attempting to compare the performance and fuel economy of different powertrain technologies, vehicle dynamics and powertrain control methods.

As CO2 legislation tightens, the next generation of turbocharged gasoline engines must meet stricter emissions targets combined with increased fuel efficiency standards. Recent studies have shown that the following technologies offer significant improvements to the efficiency of turbocharged GDI engines: Miller Cycle via late intake valve closing (LIVC), low pressure loop cooled EGR (LPL EGR), port water injection (PWI), and cylinder deactivation (CDA). While these efficiency-improving technologies are individually well-understood, in this study we directly compare these technologies to each other on the same engine at a range of operating conditions and over a range of compression ratios (CR). The technologies tested are applied to a boosted and direct injected (DI) gasoline engine and evaluated both individually and combined.

As CO2 legislation tightens, the next generation of turbocharged gasoline engines must meet stricter emissions targets combined with increased fuel efficiency standards. Promising technologies under consideration are: Miller Cycle via late intake valve closing (LIVC), low pressure loop cooled exhaust gas recirculation (LPL EGR), port water injection (PWI), and cylinder deactivation (CDA). While these efficiency improving options are well-understood individually, in this study we directly compare them to each other on the same engine at a range of operating conditions and over a range of compression ratios (CR). For this purpose we undertake a comprehensive simulation of the above technology options using a GT-Power model of the engine with a kinetics based knock combustion sub-model to optimize the fuel efficiency, taking into account the total in-cylinder dilution effects, due to internal and external EGR, on the combustion.

Prediction of power efficiency of gear boxes has become an increasingly important research topic since fuel economy requirements for passenger vehicles are more stringent, due to not only fuel cost but also environmental regulations. Under this circumstance, the automotive industry is dedicatedly focusing on developing a highly efficient gear box. Thus, the analysis of power efficiency of gear box should be performed to have a transmission that is highly efficient as much as possible at the beginning of design stage. In this study, a program is developed to analyze the efficiency of an entire gearbox, considering all components’ losses such as gear mesh, wet clutches, bearings, oil pump and so on. The analytical models are based on the formulations of each component power loss model which has been developed and published in many existing papers. The program includes power flow analysis of both a parallel gear-train and a planetary gear-train.

The design of a demonstration vehicle is presented where improvements to the electrical and air induction systems are made which provide increased performance with improved fuel economy. This is made possible by a 48 V architecture which enables the deployment of new components, specifically a belted motor generator unit (MGU) and electrically-driven compressor (eBooster®). The synergy between these components enables energy efficient means to collect regenerated energy and provide added torque, faster engine response, and extended engine off operation among a list of added features. Control features and strategy are highlighted along with simulation and vehicle test data. Resultant performance and fuel economy benefits are reviewed which support the contention of 48 V being a cost effective architecture to enable CO2 reduction relative to a higher voltage hybrid.

It has been discussed in numerous prior studies that in-neutral coasting, or sailing, can accomplish considerable amount of fuel saving when properly used. The driving maneuver basically makes the vehicle sail in neutral gear when propulsion is unnecessary. By disengaging a clutch or shifting the gear to neutral, the vehicle may better utilize its kinetic energy by avoiding dragging from the engine side. This strategy has been carried over to series production recently in some of the vehicles on the market and has become one of the eco-mode features available in current vehicles. However, the duration of coasting must be long enough to attain more fuel economy benefit than Deceleration Fuel Cut-Off (DFCO) - which exists in all current vehicle powertrain controllers - can bring. Also, the transients during shifting back to drive gear can result in a drivability concern.

In a divided-exhaust turbocharging system, 1 exhaust valve and port from each cylinder can be directed to the turbocharger turbine (referred to as the Blowdown Path) and the other can bypass the turbocharger (referred to as the Scavenge Path). The Blowdown and Scavenge valve events are determined based on the functions of the blowdown and displacement phases of the exhaust process. In our previous publications of another version of Divided Exhaust Period Turbocharging, the Valve Event Modulated Boost system (VEMB), we demonstrated significant engine efficiency and performance improvements over the base turbocharged engine. Reductions in pumping work and high-load Residual Gas Fraction are the primary reasons for efficiency and performance improvements.