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Abstract The transition of vehicle propulsion technologies away from conventional internal combustion engines toward more electrically dominant systems such as plug-in hybrid electric vehicles (PHEV) poses new challenges for vehicle thermal management systems. Especially at low ambient temperatures, consumer demand for cabin comfort as well as legislatively imposed safety considerations significantly reduce the electric driving range because only electric energy can be used for heating during emissions-free driving modes. Recent developments to find energy efficient thermal management systems for electric and plug-in electric vehicles have led to the implementation of automotive heat pump systems. As an alternative approach to meet dynamic heating demands and safety regulations, these systems use heat at a low temperature level, for example the waste heat of electric drivetrain components, to heat the passenger compartment efficiently and therefore increase the electric driving range.

Abstract Investigation of vehicle resistant forces and power losses is of crucial importance owing to current state of energy consumption in transport sector. Meanwhile, considerable portion of resistant forces in a ground vehicle is traced back to tires. Pneumatic tires are known to be a source of energy dissipation as a consequence of their viscoelastic nature. The current study aims to provide a modification to tire resistance by considering the power loss in a tire due to longitudinal slip. The modified tire resistance is comprised of rolling resistance and a newly introduced resistance caused by tire slip, called slip resistance. The physical model is chosen for parameters sensitivity study since the tractive force is described in this model via tangible physical parameters, e.g. tire tangential stiffness, coefficient of friction, and contact patch length.

Abstract This article applies a new method for the evaluation and estimation of real-life energy consumption of two different thermal management systems based on driving behavior in the course of the day. Recent attempts to find energy-efficient thermal management systems for electric and plug-in hybrid electric vehicles have led to using secondary loop systems as an alternative approach for meeting dynamic heating and cooling demands and reducing refrigerant charge. However, the additional layer of thermal resistance, which influences the system’s transient behavior as well as passenger compartment comfort during cool-down or heat-up, makes it difficult to estimate the annual energy consumption. In this article, the overall energy consumption of a conventional and a secondary loop system is compared using a new method for describing actual customers’ driving behavior in the course of the day.

Abstract Making use of a specifically designed dynamical vehicle model, the authors here presented the results of an activity for the evaluation of energy consumption and CO2 emissions of buses for urban applications. Both conventional and innovative (series hybrid, and fully electric) vehicles were considered to obtain interesting comparative conclusions. The derived tool was used to simulate the dynamical behaviour of these vehicles on a number of kinematic profiles measured during real buses operation in different contexts, varying from really congested city centre routes to fast-lane operated services. It was so possible to evaluate the energetic performances of those buses on a Tank-to-Wheel (TTW) basis.

Abstract The development, analysis, and optimization of battery electric class-7 heavy-duty trucks equipped with multi-speed transmissions are discussed in this paper. The designs of five new traction motors-fractional-slot, concentrated winding machines-are proposed for use in heavy-duty electric trucks. The procedure for gear-ratio range selection is outlined and ranges of gear ratios for three-to six-speed transmission powertrains are calculated for each of the proposed electric traction motors. The simulation and gear-ratio optimization tasks for class-7 battery electric trucks are formulated. The energy consumption of the e-truck with the twenty possible powertrain combinations is minimized over the four driving cycles and the most efficient powertrain layouts that meet the performance criteria are recommended.

Abstract 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. This is due to the fact that DP that offers the global optimal solution requires the pre-known knowledge of the driving condition for the whole drive cycle, which makes the real-time implementation of the strategy more challenging. 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.

Abstract From the fact that a propulsor consumes less power for a given thrust if the inlet air is slower, simulations are conducted for a propulsor imposed behind an airfoil as ideal boundary layer ingestion (BLI) propulsor to stand on the benefits of this configuration from the point of view of power and efficiency and to get a closer look on the mutual interaction between them. This interaction is quantified by the impact on three main sets of parameters, namely, power consumption, boundary layer properties, and airfoil performance. The position and size of the propulsor have great influence on the flow around the airfoil. Parametric studies are carried out to understand their influence. BLI propulsor directly affects the power saving and all of the pressure-dependent parameters, including lift and drag. For the present case, power saving reached 14.4% compared to the propeller working in freestream.

Abstract This study investigates methods to precisely control a coolant pump in an internal combustion engine. The goal of this research is to minimize power consumption while still meeting optimal performance, reliability and durability requirements for an engine at all engine-operating conditions. This investigation achieves reduced fuel consumption, reduced emissions, and improved powertrain performance. Secondary impacts include cleaner air for the earth, reduced operating costs for the owner, and compliance with US regulatory requirements. The study utilizes mathematical modeling of the cooling system using heat transfer, pump laws, and boiling analysis to set limits to the cooling system and predict performance changes.

Abstract Catalytic converters, a primary component in most automotive emissions control systems, do not function well until they are heated substantially above ambient temperature. As the primary energy for catalyst heating comes from engine exhaust gases, plug-in hybrid electric vehicles (PHEVs) that have the potential for short and infrequent use of their onboard engine may have limited energy available for catalytic converter heating. This article presents a comparison of multiple hybrid supervisory control strategies to determine the ability to avoid engine cold starts during a blended charge-depleting propulsion mode. Full vehicle and catalytic converter simulations are performed in parallel with engine dynamometer testing in order to examine catalyst temperature variations during the course of the US06 City drive cycle. Emissions and energy consumption (E&EC) calculations are also performed to determine the effective number of engine starts during the drive cycle.

Abstract A dynamic model of a multi-unit air conditioning (AC) system in a generic bus was developed to investigate different control strategies on the system performance and the cabin comfort level. In this study, a part-load condition was considered, where adopting a proper strategy for governing a multi-unit system is important. Simulink and Simscape toolbox from MATLAB (R2019a) were used to build up the real-time model by integrating a cooling system with a cabin sub-model. The cooling system consists of two independently controlled units, based on a Vapor Compression Cycle (VCC). The cabin is modelled using a moisture air network and is coupled with the cooling system to exchange heat with the refrigerant through the evaporators. Moreover, the sensible and latent loads are incorporated into the cabin by a thermal network.

Abstract Reactivity-controlled compression ignition (RCCI) is a dual fuel low temperature combustion (LTC) strategy which results in a wider operating load range, near-zero oxides of nitrogen (NOx) and particulate matter (PM) emissions, and higher thermal efficiency. One of the major shortcomings in RCCI is a higher unburned hydrocarbon (HC) and carbon monoxide (CO) emissions. Unlike conventional combustion, aftertreatment control of HC and CO emissions is difficult to achieve in RCCI owing to lower exhaust gas temperatures. In conventional RCCI, an early direct injection (DI) of low volatile diesel fuel into the premixed gasoline-air mixture in the combustion chamber results in charge stratification and fuel spray wall wetting leading to higher HC and CO emissions. To address this limitation, a homogeneous charge reactivity-controlled compression ignition (HCRCCI) strategy is proposed in the present work, wherein the DI of diesel fuel is eliminated.

Abstract Fan cooling system of an air-cooled diesel engine is optimized using 3D CFD numerical simulation approach. The main objective of this article is to increase engine fuel efficiency by reducing fan power consumption. It is achieved by optimizing airflow rates and flow distribution over the engine surfaces to keep the maximum temperature of engine oil and engine surfaces well within the lubrication and material limit, respectively, at the expense of lower fan power. Based on basic fan laws, a bigger fan consumes lesser power for the same airflow rate as compared to a smaller fan, provided both fans have similar efficiency. Flow analysis is also conducted with the engine head and block modeled as solid medium and fan cooling system as fluid domain. Reynolds-averaged Navier-Stokes turbulence (RANS) equations were solved to get the flow field inside the cooling system and on the engine liner fins. The Moving Reference Frame approach was used for simulating the rotation of a fan.

Abstract This article describes the application of Reinforcement Learning (RL) with an embedded heuristic algorithm to a multi-objective hybrid vehicle optimization. A multi-objective optimization problem (MOP) is defined as a minimization of total energy consumption and trip time resulting from optimal control of vehicle speed over a known route. First, a computationally efficient heuristic optimization algorithm is formulated to solve the MOP for multiple traffic scenarios. Then, the off-line integration of RL is applied to the heuristic optimization algorithm process and utilized to solve the MOP. Finally, the online optimization capability of the machine learning algorithm is discussed, as well as its extension to the vehicle routing problem and the hybrid electric vehicle. The specific scenario investigated is where a generic vehicle begins a trip on a one-lane highway. The length of the highway and the number of vehicles and traffic signals on the road are generic as well.

Abstract With highway vehicles using over 20% of the total energy consumption in the United States, making strides in improving their fuel economy will positively influence the nation’s environmental impact. One methodology to accomplish this outcome is by reducing vehicle weight. In this regard, since the internal combustion (IC) engine is a major contributor to the mass of an automobile, it is an ideal area to target. Prior efforts in this area include using alternative materials (e.g., aluminum or magnesium) to decrease weight. Here, additive manufacturing (AM) is an appealing option due to its freedom from typical manufacturing constraints and the ability to produce highly optimized designs using nonconventional powertrain materials (e.g., titanium). The use of AM has the potential to increase reliability, improve performance, decrease production cost, and possibly minimize the number of parts.

Abstract Currently, the governments are encouraging automotive vehicle manufacturers to produce electric vehicles (EVs) as these vehicles have a zero-emission footprint. Generally, the EVs are expected to be quieter compared to internal combustion engine (ICE) vehicles. But the absence of engine noise in EVs brings more challenges for noise, vibration, and harshness (NVH) as the other noise sources become more audible. Most of these noise sources are tonal in nature and, hence, cause discomfort to the passengers. The present work is related to the noise refinement in a pure EV. The dominant noise sources observed in this vehicle are the electric powertrain, cooling fan, and air compressor. The powertrain consists of a traction motor and a gearbox (GB) with a planetary gear system. The root cause identification of electric powertrain noise has been investigated with masking trials and with the acoustic camera.

Abstract The main technical barrier to commercial use of microturbines is its low efficiency, not exceeding 15%. Efficiency and specific power are as high as the Turbine Inlet Temperature (TIT), generally limited to 950°C in microturbines, as its tiny rotors make internal blade cooling impossible. This work uses Computational Fluid Dynamics (CFD) to develop an external cooling system of the blades of a microturbine by incorporating a compressor into the disk to blow air over the blades’ walls. The engine used as the basis of the work is the FD-3/64. The work was divided into two steps. In the first, Step 1, the reactive flow in the combustor was simulated to obtain the boundary conditions for Step 2. In Step 2, the flow through the turbine wheel during rotation is simulated. Four rotor models were simulated.

Abstract TOC

Abstract Turbocharging can provide a low cost means for increasing the power output and fuel economy of an internal combustion engine. Currently, turbocharging is common in multi-cylinder engines, but due to the inconsistent nature of intake air flow, it is not commonly used in single-cylinder engines. In this article, we propose a novel method for turbocharging single-cylinder, four-stroke engines. Our method adds an air capacitor-an additional volume in series with the intake manifold, between the turbocharger compressor and the engine intake-to buffer the output from the turbocharger compressor and deliver pressurized air during the intake stroke. We analyzed the theoretical feasibility of air capacitor-based turbocharging for a single-cylinder engine, focusing on fill time, optimal volume, density gain, and thermal effects due to adiabatic compression of the intake air.

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 In current production natural gas/gasoline bi-fuel vehicles, fuels are supplied via port fuel injection (PFI). Injecting a gaseous fuel in the intake port significantly reduces the volumetric efficiency and consequently torque as compared to gasoline. In addition to eliminating the volumetric efficiency challenge, direct injection (DI) of natural gas (NG) can enhance the in-cylinder flow, mixing, and combustion process resulting in improved efficiency and performance. A computational fluid dynamics (CFD) approach to model high-pressure gaseous injection was developed and validated against X-ray data from Argonne’s Advanced Photon Source. NG side and central DI of various designs and injection strategies were assessed experimentally along with CFD correlation. Significant effects on combustion metrics were quantified and explained via improved understanding of the in-cylinder flow effects due to NG injection.