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Abstract Energy management strategies for charge-sustaining hybrid electric vehicles reduce fuel consumption and maintain battery pack state of charge while meeting driver output power demand. The equivalent consumption minimization strategy is a real-time energy management strategy that makes use of an equivalence ratio to quantify electric power consumption in terms of fuel power consumption. The magnitude of the equivalence ratio determines the hybrid electric vehicle mode of operation and influences the ability of the energy management strategy to reduce fuel consumption as well as maintain the battery pack state of charge. The equivalent consumption minimization strategy in this article uses three Willans line models, which have an associated marginal efficiency and constant offset, to model the performance in the hybrid electric vehicle controller.

Abstract The variability of fuel economy (FE) is of significant importance as that of average FE to realize FE benefits of hybrid electric vehicles (HEVs) consistently by all users in the real world. Over the years, majority of the research has been focused on improving average FE overlooking the variability. Although in recent years few studies have been focused on the reduction of FE variability, no study has been concentrated to understand why certain design has lower FE variability as that of others. This article provides a detailed analysis to decipher the reasons for the FE variability in the real world. This study considered the optimum designs based on two established design optimization methodologies considering Toyota Prius non-plug-in hybrid as a base vehicle. This study analyses the impacts of the parameters of driving patterns and the operation of powertrains on FE variability.

Abstract To reduce fuel consumption and carbon dioxide (CO2) emissions from mobile air conditioning (A/C) systems, “U.S. Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards” identified solar/thermal technologies such as solar control glazings, solar reflective paint, and active and passive cabin ventilation in an off-cycle credit menu. National Renewable Energy Laboratory (NREL) researchers developed a sophisticated analysis process to calculate U.S. light-duty A/C fuel use that was used to assess the impact of these technologies, leveraging thermal and vehicle simulation analysis tools developed under previous U.S. Department of Energy projects. Representative U.S. light-duty driving behaviors and weighting factors including time-of-day of travel, trip duration, and time between trips were characterized and integrated into the analysis.

Abstract Low-Pressure cooled Exhaust Gas Recirculation (LP-cEGR) is proven to be an effective technology for fuel efficiency improvement in turbocharged spark-ignition (SI) engines. Aiming to fully exploit the EGR benefits, new challenges are introduced that require more complex and robust control systems and strategies. One of the most important restrictions of LP-cEGR is the transient response, since long air-EGR flow paths introduce significant transport delays between the EGR valve and the cylinders. High dilution generally increases efficiency, but can lead to cycle-by-cycle combustion variation. Especially in SI engines, higher-than-requested EGR dilution may lead to combustion instabilities and misfires. Considering the long EGR evacuation period, one of the most challenging transient events is throttle tip-out, where the engine operation shifts from a high-load point with high dilution tolerance to a low-load point where EGR tolerance is significantly reduced.

Abstract Autonomy and connectivity are considered among the most promising technologies to improve safety and mobility and reduce fuel consumption and travel delay in transportation systems. In this paper, we devise an optimal control-based trajectory planning model that can provide safe and efficient trajectories for the subject vehicle while incorporating platoon formation and lane-changing decisions. We embed this trajectory planning model in a simulation framework to quantify its fuel efficiency and travel time reduction benefits for the subject vehicle in a dynamic traffic environment. Specifically, we compare and analyze the statistical performance of different controller designs in which lane changing or platooning may be enabled, under different values of time (VoTs) for travelers.

Abstract Modern vehicles have incorporated numerous safety-focused advanced driver-assistance systems (ADAS) in the last decade including smart cruise control and object avoidance. In this article, we aim to go beyond using ADAS for safety and propose to use ADAS technology to enable predictive optimal energy management and improve vehicle fuel economy (FE). We combine ADAS sensor data with a previously developed prediction model, dynamic programming (DP) optimal energy management control, and a validated model of a 2010 Toyota Prius to explore FE. First, a unique ADAS detection scope is defined based on optimal vehicle control prediction aspects demonstrated to be relevant from the literature. Next, during real-world city and highway drive cycles in Denver, Colorado, a camera is used to record video footage of the vehicle environment and define ADAS detection ground truth. Then, various ADAS algorithms are combined, modified, and compared to the ground truth results.

Abstract Wheel loaders are widely used in construction projects. In order to reduce pollution and energy consumption, major wheel loader manufacturers are developing electric powertrain technology. Our main research goal is to reduce the energy consumption of a pure electric loader. This study is intended to build a vehicle simulation model of a multiple drive motor electric loader. According to the common working conditions and empirical formulas of the loader, the simulation data of the electric loader are calculated. The torque distribution control strategy based on the optimal efficiency of the motor is designed for the multiple drive motor electric loader and is compared with the equal proportion distribution control and the axle load ratio distribution control through simulation analysis. The simulation results show that the proposed torque distribution control strategy based on motor optimal efficiency can reduce energy consumption by 7–12%.

Abstract The National Academies’ 2021 Automotive Fuel Economy Report: Commendable Progress and Missed Opportunity

Abstract The article describes the results achieved in developing a new diesel combustion system for passenger car application that, while capable of high power density, delivers excellent fuel economy through a combination of mechanical and thermodynamic efficiencies improvement. The project stemmed from the idea that, by leveraging the high fuel injection pressure of last generation common rail systems, it is possible to reduce the engine peak firing pressure (pfp) with great benefits on reciprocating and rotating components’ light-weighting and friction for high-speed light-duty engines, while keeping the power density at competitive levels. To this aim, an advanced injection system concept capable of injection pressure greater than 2500 bar was coupled to a prototype engine featuring newly developed combustion system. Then, the matching among these features has been thoroughly experimentally examined.

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Abstract Numerous works have been carried out with perspectives to improve the energy efficiency of electric vehicle (EV) drivetrains; much of the attention has been on the design of highly efficient electric motors, power converters, and energy storage system. Besides the abovementioned factors, selection of the drivetrain configuration and control strategy also influence the efficiency and performance of EV drivetrain. The drivetrain efficiency and performance indices, such as torque ripple and total harmonic distortion (THD) of voltage and current, are sensitive to the direct current (dc)-link voltage and flux linkage values for a drivetrain control strategy. Therefore, in this work, the efficiency and the performance of two popular direct torque controlled induction motor (IM) drives are compared on the basis of adjustable dc-link voltage and flux linkage values for desired operating condition. Both these techniques are implemented on a lab scale test bed.

Abstract Gasoline direct-injection (GDI) engines are increasing market penetration. They are attractive because they substantially decrease CO2 emissions and can increase fuel economy. However, due to their design, GDI engines are prone to increases in soot production. Blends of alcohols with gasoline have been observed to decrease soot production in GDI engines. However, results have been mixed, with publications suggesting either a decrease or an increase in soot production. Recent publications have indicated that increases in soot production are tied to fuel impingement onto the cylinder head during high-load engine periods. The work presented here utilizes an equation of state (EoS) model to understand the volatility characteristics of oxygenate-surrogate fuel blends, focusing on the volatility of aromatics. EoS calculations are rapid, and allow for the simulation of a broad range of temperatures and pressures.

Abstract Driving schedule of every vehicle involves transient operation in the form of changing engine speed and load conditions, which are relatively unchanged during steady-state conditions. As well, the results from transient conditions are more likely to reflect the reality. So, the current research article is focused on analyzing the biofuel-like lemon peel oil (LPO) behavior under real-world transient conditions with fuel injection parameter MAP developed from steady-state experiments. At first, engine parameters and response MAPs are developed by using a response surface methodology (RSM)-based multi-objective optimization technique. Then, the vehicle model has been developed by incorporating real-world transient operating conditions. Finally, the developed injection parameters and response MAPs are embedded in the vehicle model to analyze the biofuel behavior under transient operating conditions.

Abstract An optimization method of a shifting strategy for a hybrid electric vehicle (HEV) is proposed in this article. Firstly, the basic idea of the shifting strategy is introduced. Then the differences of powertrain between a parallel HEV and fuel vehicle are analyzed, and a design method of the shifting strategy for parallel HEV is proposed. Finally, the whole vehicle simulation model is established by using Matlab/Simulink software, and the results are compared with the shifting strategy of fuel vehicles. The simulation results show that the fuel economy of the parallel HEV is significantly improved.

Abstract The mechanical efficiency of the current continuously variable transmission (CVT) suffers from high pump loss induced by a high-pressure system. A novel wedge mechanism is designed into the CVT clamp actuation system to generate the majority of clamp force mechanically. Therefore, the hydraulic system can operate at a low-pressure level most of the time, and the pump loss is greatly reduced to improve the CVT’s mechanical efficiency. Through dynamic analysis and design optimization, 90% of clamp force is contributed by the wedge mechanism and the rest of the 10% is generated by a conventional hydraulic system. The optimal design is validated through dynamic modeling using Siemens Virtual.Lab software by simulating the wedge clamp force generation, ratio change dynamics, and system response under tip-in conditions. After that, we built prototype components that target 70% of the clamp force contributed by the wedge mechanism and tested them on a transmission dynamometer.

Abstract The pursuit of improved fuel economy through weight reduction, reduced manufacturing costs, and improved crash safety can result in increased compliance in automobile structures. However, with compliance comes an increased susceptibility to aerodynamic and vibratory loads. The hood in particular withstands considerable aerodynamic force at highway speeds, creating the potential for significant aeroelastic response that may adversely impact customer satisfaction and perception of vehicle quality. This work seeks an improved understanding in computational and experimental study of fluid-structure interactions between automobile hoods and the surrounding internal and external flow. Computational analysis was carried out using coupled CFD-FEM solvers with detailed models of the automobile topology and structural components. The experimental work consisted of wind tunnel tests using a full-scale production vehicle.

Abstract When commercial vehicles drive in a mountainous area, the complex road condition and long slopes cause frequent acceleration and braking, which will use 25% more fuel. And the brake temperature rises rapidly due to continuous braking on the long-distance downslopes, which will make the brake drum fail with the brake temperature exceeding 308°C [1]. Meanwhile, the kinetic energy is wasted during the driving progress on the slopes when the vehicle rolls up and down. Our laboratory built a model that could calculate the distance from the top of the slope, where the driver could release the accelerator pedal. Thus, on the slope, the vehicle uses less fuel when it rolls up and less brakes when down. What we do in this article is use this model in a real vehicle and measure how well it works.

Abstract Commercial vehicles require continual improvements in order to meet fuel consumption standards, improve diesel aftertreatment (AT) system performance, and optimize vehicle fuel economy. Simultaneous reductions in both CO2 and NOX emissions will be required to meet the upcoming regulatory targets for both EPA Phase 2 Greenhouse Gas Standards and new Low NOX Standards being proposed by the California Air Resources Board (CARB). In addition, CARB recently proposed a new certification cycle that will require high NOX conversion while vehicles are operating at lower loads than current regulatory cycles require. Cylinder deactivation (CDA) offers a powerful technology lever for meeting these two regulatory targets on commercial diesel engines. There have been numerous works in the past year showing the benefits of diesel CDA for elevating exhaust temperatures during low-load operation where it is normally too cold for AT to function at peak efficiency.

Abstract Under high-speed working conditions of an engine, the lubrication and tribological performance (LTP) of the crankpin bearing (CB) are strongly influenced by the oil film pressure (p) and asperity contact in the mixed lubrication regime (MLR) of CB, while these parameters mainly depend on the CB’s geometrical dimensions including the bearing radius (r b), bearing width (B), surface roughness (σ), gap between crankpin and bearing (c), and crankpin speed (ω). To analyze the sensitivity of the dynamic parameters of the r b, B, σ, c, and ω on the CB’s LTP, a hybrid model of the piston-rod-crank dynamic and CB lubrication is proposed to establish the dynamic equations of the CB. An algorithm program written in MATLAB software is then applied to solve the dynamic equations. The effect of the dynamic parameters of the r b, B, σ, c, and ω on the CB’s LTP is simulated and evaluated via the indexes of the p, asperity contact force, friction force, and friction coefficient.