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Power split in Fuel Cell Hybrid Electric Vehicles (FCHEVs) has been controlled using different strategies ranging from rule-based to optimal control. Dynamic Programming (DP) and Model Predictive Control (MPC) are two common optimal control strategies used in optimization of the power split in FCHEVs with a trade-off between global optimality of the solution and online implementation of the controller. In this paper, both control strategies are developed and tested on a FC/battery vehicle model, and the results are compared in terms of total energy consumption. In addition, the effects of the MPC prediction horizon length on the controller performance are studied. Results show that by using the DP strategy, up to 12% less total energy consumption is achieved compared to MPC for a charge sustaining mode in the Urban Dynamometer Driving Schedule (UDDS) drive cycle.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

Trucks can carry heavy load and when applying the brakes during for example a mountain downhill or for an abrupt stop, the brake temperatures can rise significantly. Elevated temperatures in the drum brake region can reduce the braking efficiency or can even cause the brake system to fail, catch fire or even break. It therefore needs to be designed such to be able to transfer the heat out of its system by convection, conduction and/or radiation. All three heat transfer modes play an important role since the drum brakes of trucks are not much exposed to external airflow, a significant difference from disk brakes of passenger cars analyzed in previous studies. This makes it a complex heat transfer problem which is not easy to understand. Numerical methods provide insight by visualization of the different heat transfer modes. Presented is a numerical method that simulates the transient heat transfer of a truck drum brake system cooldown at constant driving speed.

The study of spray-wall interaction is of great importance to understand the dynamics during fuel-surface impingement process in modern internal combustion engines. The identification of droplet post-impingement pattern (contact, transition, non-contact) and droplet characteristics can quantitatively provide an estimation of energy transfer for spray-wall interaction, thus further influencing air-fuel mixing and emissions under combusting conditions. Theoretical criteria of single droplet post-impingement pattern on a dry wall have been experimentally and numerically studied by many researchers to quantify the hydrodynamic droplet behaviors. However, apart from model fidelity, another issue is the scalability. A theoretical criterion developed from one case might not be well suited to another scenario. In this paper, a data-driven approach for single droplet-dry wall post-impingement pattern utilizing arithmetical machine learning classification methods is proposed and demonstrated.

The successful implementation of a clean, quiet, high-performance four-stroke motorcycle engine into an existing snowmobile chassis has been achieved. The snowmobile is easy to start, easy to drive, and environmentally friendly. The following paper describes the conversion process in detail with actual dynamometer and field test data. The vehicle meets the proposed 2010 EPA snowmobile emissions regulations and is quieter than a stock snowmobile. The snowmobile not only addresses environmental concerns, it is economical as well, with an approximate cost of $5874.

Modern aerodynamic Class 8 freight tractors can improve vehicle freight efficiency and fuel economy versus older traditional style tractors when pulling Canadian style A- or B-Train double trailer long combination vehicles (LCV's) at highway speeds. This paper compares the aerodynamic performance of a current generation aerodynamic tractor with several freight hauling configurations through computational fluid dynamics evaluations using the Lattice-Boltzmann methodology. The configurations investigated include the tractor hauling a standard 53′ trailer, a platooning configuration with a 30′ separation distance, and an A-Train configuration including two 48′ trailers connected with a dolly converter. The study demonstrates CFD's capability of evaluating extremely long vehicle combinations that might be difficult to accomplish in traditional wind tunnels due to size limitations.

The increasing importance of reducing greenhouse gas emissions and the ongoing evolution of vehicle-to-vehicle connectivity technologies have generated significant interest in platooning for commercial vehicles, where two or more vehicles travel in same traffic lane in relatively close proximity. This paper examines the effect of platooning on four increasingly aerodynamic tractor-trailer configurations, using a Lattice Boltzmann based CFD solver. Each platoon consisted of three identical tractor-trailer configurations traveling in the same lane at 65mph. Two different vehicle to vehicle gaps were studied, 5m and 9m, in addition to singleton (solitary) vehicles, representing an effectively infinite gap. Aerodynamic drag for the lead, middle, and trailing vehicle in the platooning configurations were compared to the corresponding single vehicle tractor-trailer configuration.

As part of the United States Department of Energy's SuperTruck program, Volvo Trucks and its partners were tasked with demonstrating 50% improvement in overall freight efficiency for a tractor-trailer, relative to a best in class 2009 model year truck. This necessitated that significant gains be made in reducing aerodynamic drag of the tractor-trailer system, so trailer side-skirts and a trailer boat-tail were employed. A Lattice-Boltzmann based simulation method was used in conjunction with a Kriging Response Surface optimization process in order to efficiently describe a design space of seven independent parameters relating to boat-tail and side-skirt dimensions, and to find an optimal configuration. Part 1 concerns a fully-skirted tractor-trailer system, and consists of an initial phase of optimization, followed by a mid-project re-evaluation of constraints, and an additional period of optimization.

Aerodynamic performance assessment of automotive shapes is typically performed in wind tunnels. However, with the rapid progress in computer hardware technology and the maturity and accuracy of Computational Fluid Dynamics (CFD) software packages, evaluation of the production-level automotive shapes using a digital process has become a reality. As the time to market shrinks, automakers are adopting a digital design process for vehicle development. This has elevated the accuracy requirements on the flow simulation software, so that it can be used effectively in the production environment. Evaluation of aerodynamic performance covers prediction of the aerodynamic coefficients such as drag, lift, side force and also lift balance between the front and rear axle. Drag prediction accuracy is important for meeting fuel efficiency targets, prediction of front and rear lifts as well as side force and yawing moment are crucial for high speed handling.

The accuracy of the Lattice-Boltzmann based simulation method for prediction of aerodynamic drag on a heavy truck was evaluated by comparing results to twenty percent scale model wind tunnel measurements from the University of Washington Aeronautical Laboratory (UWAL). A detailed preproduction Kenworth T2000 tractor trailer was used as the scale model. The results include a comparison of normalized drag between simulation and wind tunnel as well as percentage drag change with the addition of a radius to the rear edge of the trailer. Significant effort was involved to model all of the wind tunnel details affecting the tractor-trailer drag. These are discussed along with the results of additional simulations which were performed to study the impact of the UWAL tunnel geometry relative to a tunnel with the same blockage and constant cross-sectional area, and a case with negligible blockage.

Aerodynamic simulations of a 1:8-scale simplified tractor-trailer, designated as the Generic Conventional Model (GCM), were conducted using a Lattice-Boltzmann based solver. Comparisons were made to experimental measurements from the NASA Ames 12-Foot Pressure Wind Tunnel, including drag coefficients as a function of yaw, static and transient surface pressures, and three-component particle image velocimetry. The baseline model configuration was tested at yaw angles from 0 to 12 degrees, allowing the calculation of the wind-averaged drag coefficient. Results demonstrated that the simulation predicted body-axis drag within experimental uncertainty and also resolved the correct pressure distribution and flow structure in the separated flow regions including the tractor-trailer gap and trailer wake regions. The comparison of the experimental transient pressure spectra showed good agreement with the simulation results, both in magnitude and identification of dominant spectral peaks.

The importance of fuel economy and emission standards has increased rapidly with high fuel costs and new environmental regulations. This requires analysis techniques capable of designing the next generation long-haul truck to improve both fuel efficiency and cooling. In particular, it is important to have a predictive design tool to assess how exterior design changes impact aerodynamic performance. This study evaluates the use of a Lattice Boltzmann based numerical simulation and the National Research Council (NRC) Canada's wind tunnel to assess aerodynamic drag on a production Volvo VNL tractor-trailer combination. Comparisons are made between the wind tunnel and simulation to understand the influence of wind tunnel conditions on truck aerodynamic performance. The production VNL testing includes a full range of yaw angles to demonstrate the influence of cross wind on aerodynamic drag.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

Homogenous charge compression ignition (HCCI) engines offer a great potential in achieving high thermal efficiency and extremely low NOx at the same time. However, control of combustion phasing over a wide speed and load range has been a challenge, especially during transient operations. This paper describes work conducted at the National Vehicle and Fuel Emissions Laboratory, which explores the potential use of an HCCI engine as a power plant for a hybrid vehicle. A four-cylinder, 1.9 L commercial diesel engine was modified to operate with port-injected regular grade gasoline in HCCI mode. The combustion phasing is controlled by a combination of boost, EGR and thermal management as a function of engine speed and load. As a stand-alone unit, the engine has demonstrated a wide operation range with efficiency like that of a diesel engine and NOx below 0.2 g/kWh. At room temperature, the engine starts in SI mode and then transitions to HCCI in about 25 seconds.

Low Temperature Combustion (LTC) engines are promising to improve powertrain fuel economy and reduce NOx and soot emissions by improving the in-cylinder combustion process. However, the narrow operating range of LTC engines limits the use of these engines in conventional powertrains. The engine’s limited operating range can be improved by taking advantage of electrification in the powertrain. In this study, a multi-mode LTC-SI engine is integrated with a parallel hybrid electric configuration, where the engine operation modes include Homogeneous Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), and conventional Spark Ignition (SI). The powertrain controller is designed to enable switching among different modes, with minimum fuel penalty for transient engine operations.

The scope of this paper is to describe how system level NVH targets are cascaded down to sub system level targets using the technique of Transfer Path Analysis (TPA). In the early stages of a vehicle design program target vehicles for the new vehicle are selected based on their subjective Noise, Vibration, and Harshness (NVH) performance. A reference vehicle for the new product will be selected which will be used as a baseline vehicle for the whole vehicle program. Noise and vibration measurements will be taken on both the reference and target vehicles under multiple load conditions. The simulation target for the new product will be derived from the measurements of reference vehicle, measurements of target vehicle, and the simulation of reference vehicle model. Reverse Transfer Path Analysis tools will be used to quantify the subsystem targets for the new vehicle based on the simulation targets and design intent simulation models of new product.

Aerodynamic evaluation of vehicles using static yaw angle changes in wind tunnel testing and numerical simulation has been used as standard practice for evaluating vehicle performance under a range of wind conditions. However, this approach does not consider dynamic wind effects coming from changing wind conditions, passing other vehicles and roadside obstacles, and transient non-uniform wind conditions coming from environmental turbulence. In previous work by the authors, computational fluid dynamics (CFD) simulation methodology for considering dynamic wind conditions and on-road turbulence was demonstrated, showing the important effects of the wind conditions on the vehicle aerodynamics. The technique allows the vehicle to be tested under a range of transient gust conditions, also accounting for wind turbulence coming from upstream vehicles and natural environmental wind fluctuations.

In light-duty vehicles, there is a fundamental trade-off between fuel consumption and acceleration performance, if other vehicle attributes are held fixed. Earlier econometric studies have estimated the magnitude of this trade-off - the elasticity of fuel consumption with respect to performance - based on historical vehicle data. The majority of these studies assume, a priori, that elasticity is constant across the model year, vehicle power, and technology content. However, there is evidence that the content in the underlying powertrain technology packages is shifting in a way that reduces the value of the elasticity of fuel consumption with respect to performance, such that historical trends would not predict future behavior. This paper presents an alternative strategy for studying vehicle fuel consumption versus performance trade-off.

Increasing regulatory demand to reduce CO2 emissions has led to an industry focus on electrified vehicles while limiting the development of conventional internal combustion engine (ICE) and hybrid powertrains. Hybrid electric vehicle (HEV) powertrains rely on conventional SI mode IC engines that are optimized for a narrow operating range. Advanced combustion strategies such as Gasoline Compression Ignition (GCI) have been demonstrated by several others including the authors to improve brake thermal efficiency compared to both gasoline SI and Diesel CI modes. Soot and NOx emissions are also reduced significantly by using gasoline instead of diesel in GCI engines due to differences in composition, fuel properties, and reactivity. In this work, an HEV system was proposed utilizing a multi-mode GCI based ICE combined with a HEV components (e-motor, battery, and invertor).

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.