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Abstract The development of a long-term sustainable hydrogen energy economy for commercial vehicle transportation will need to overcome key critical technical and logistics considerations in the near term. As compared to zero-emission powertrains, fossil-fuel-based powertrains provide mission flexibility and high uptime at a comparatively low total cost of ownership (TCO). While the incumbent carbon-intensive powertrains suffer from poor efficiency and are not sustainable to support global climate change initiatives in transportation decarbonization, techno-economic challenges continue to create complex barriers to the large-scale displacement of these with highly electrified powertrains architectures. This article specifically addresses opportunities that well-targeted subsidies would afford in achieving fuel cell electric powertrain financial parity with diesel powertrains in heavy-duty trucks (HDTs).

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 Combustion engines and liquid fuels are likely to continue playing a central role in freight transportation with renewable fuels reducing carbon emissions. Ethanol and methanol are future renewable fuels with a knock resistance that make them suitable for heavy-duty (HD) spark ignition (SI) engines. This simulation work focuses on the potential for improving the efficiency of an ethanol- and methanol-fueled HD SI engine using early intake valve closing Miller valve timing. With Miller valve timing, the expansion ratio and thermodynamic efficiency can be increased while maintaining the same effective compression ratio. However, Miller timing requires increased boost pressure to retain the same trapped air mass and also suffers from reduced in-cylinder turbulence.

Abstract High load (18 bar IMEP) dual fuel combustion of a premixed natural gas/air charge ignited by directly injected diesel fuel was studied in a large bore gas engine. A nozzle design with low flow rate was installed to inject a small diesel volume (10.4 mm3) equal an energetic amount of about two percent. The effect of compression end temperature on ignition and combustion was investigated using valve timings with early IVC (Miller) and maximum charging efficiency (MaxCC). Furthermore, the engine speed was reduced (1500 rpm to 1000 rpm) for the Miller valve timing to analyze the impact of the chemical time scale on the combustion process. During all experiments, the cylinder charge density was kept constant adjusting the intake pressure and the resulting air mass flow.

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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 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 Previous studies have shown that injector aging adversely affects the diesel engine spray formation and combustion. It has also been shown that the oxygenated fuel additive tripropylene glycol monomethyl ether (TPGME) can lower soot emissions. In this study, the effects of injector aging and TPGME on the late-cycle oxidation of soot were investigated using laser diagnostic techniques in a light-duty optical diesel engine at two load conditions. The engine was equipped with a quartz piston with the same complex piston geometry as a production engine. Planar laser-induced incandescence (LII) was used to obtain semiquantitative in-cylinder two-dimensional (2D) soot volume fraction (fv ) distributions using extinction measurements. The soot oxidation rate was estimated from the decay rate of the in-cylinder soot concentration for differently aged injectors and for cases with and without TPGME in the fuel.

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 Hybrid Electric Vehicles (HEVs) achieve better fuel economy than conventional vehicles by utilizing two different power sources: an internal combustion engine and an electrical motor. The power distribution between these two components must be controlled using some algorithm, be it rule based, optimization based, or reinforcement learning based. In the design of such control algorithms, it is important to evaluate the impact that variations of certain design parameters will have on the system performance, in this case, fuel economy. Traditional methods of sensitivity analysis have been applied to various power flow control algorithms to determine their robustness to the variations of HEV design parameters. This article presents a sensitivity analysis of three power flow control algorithms: twin delayed deep deterministic policy gradient (TD3), deep deterministic policy gradient (DDPG), and adaptive equivalent consumption minimization strategy (A-ECMS).

Abstract Vehicle platooning reduces fuel consumption, improves traffic throughput, and achieves smaller intervehicle spacing which increases the probability of danger during platoon braking. This article presents a sliding mode control based on the safety spacing policy for longitudinal control of a connected truck platoon with a focus on the predecessor following interactions. In particular, the modified safety spacing policy considering the intervehicle braking information communication delay, the sluggish nature of the brake actuator, the road conditions on each vehicle as well as the vehicle motion state is proposed. On this basis, an acceleration sliding mode controller is proposed, which takes into consideration the spacing error and speed error of the intervehicle, and the control error is zero, so as to obtain the expected acceleration of each vehicle in the platoon.

Abstract This article investigates the ability of data-driven models to estimate instantaneous fuel consumption over 1 km road segments from different routes for different heavy-duty vehicles from the same fleet. Models are created using three different techniques: parametric, linear regression, and artificial neural networks. The proposed models use features derived from vehicle speed, mass, and road grade, which can be easily obtained from telematics devices, in addition to power take-off (PTO) active time, which is needed to capture the power requested by accessories in several heavy-duty vehicles. The robustness of these models with respect to the training data selection is improved by using k-fold cross-validation. Moreover, the inherent underestimation or overestimation bias of the model is calculated and used to offset the fuel consumption estimates for new routes. The study shows that the target application dictates the choice of model features.

Abstract The future of heavy trucking will require greater aerodynamic improvements and will involve active and automated systems that tailor varied parameters to optimize energy efficiency over a broad operational range. Continuous advancement of accuracy and precision is needed to realize these ever-smaller aerodynamic gains and to generate more detailed aerodynamic characterizations to feed these system-wide optimizations. To accomplish this, a comprehensive aerodynamic development approach is needed and should include computational fluid dynamics, operational testing, and wind tunnel testing. In 2016, a high-fidelity 1/3 scale wind tunnel model of a tractor-trailer heavy truck was developed for Reynolds equivalent wind tunnel testing with full coverage rolling road ground simulation. The model and support system were designed and built for use in the Windshear rolling road wind tunnel.

Abstract Asymmetric twin-scroll turbocharging technology, as one of the effective technologies for balancing fuel economy and nitrogen oxide emissions, has been widely studied in the past decade. In response to the ever-increasing demands for improved fuel efficiency and reduced exhaust emissions, extensive research efforts have been dedicated to investigating various aspects of this technology. Researchers have conducted both experimental and simulation studies to delve into the intricate flow mechanism of asymmetric twin-scroll turbines. Furthermore, considerable attention has been given to exploring the optimal matching between asymmetric twin-scroll turbines and engines, as well as devising innovative flow control methods for these turbines. Additionally, researchers have sought to comprehend the impact of exhaust pulse flow on the performance of asymmetric twin-scroll turbines.

Abstract In view of the traditional constant spacing policy (CSP) can’t maximize the fuel saving rate of the truck platoon when choosing the smaller desired vehicle spacing as the control target, a new control strategy is proposed in this article. This strategy dramatically reduces the fuel consumption of the truck platoon from the start to the formation of a stable platoon, thus greatly increasing the fuel saving rate of the platoon. To prove the effectiveness of the strategy, this article carried out the longitudinal dynamics modeling of the truck and the modeling of the fuel consumption model of engine first. Longitudinal dynamics modeling establishes the dynamic equations for truck braking and nonbraking. The fuel consumption model of engine is built using a three-dimensional map. Second, the design of the controller is described. The controller calculates the desired acceleration of the following vehicle based on the speed error and the following distance error.

Abstract The development of predictive maintenance has become one of the most important drivers of innovation, not only in the maritime industry. The proliferation of on-board and remote sensing and diagnostic systems is creating many new opportunities to reduce maintenance costs and increase operational stability. By predicting impending system faults and failures, proactive maintenance can be initiated to prevent loss of seaworthiness or operability. The motivation of this study is to optimize predictive maintenance in the maritime industry by determining the minimum useful remaining lead-acid battery capacity measurement frequency required to achieve cost-efficiency and desired prognostic performance in a remaining battery capacity indication system. The research seeks to balance operational stability and cost-effectiveness, providing valuable insight into the practical considerations and potential benefits of predictive maintenance.

Abstract In the last few years, reactivity-controlled compression ignition (RCCI) mode combustion has gained researchers’ attention due to its superior performance, combustion, and emission characteristics compared to other low-temperature combustion (LTC) strategies. In this study, RCCI mode combustion investigations were carried out to explore the effects of exhaust gas recirculation (EGR) and intake charge temperature (ICT) on combustion, performance, and emission characteristics of a mineral diesel/methanol-fueled engine. In this study, constant engine speed (1500 rpm) and load (3 bar brake mean effective pressure [BMEP]) were used to perform engine experiments. The premixed ratio (rp) of methanol was varied from rp = 0 to rp = 0.75, where rp = 0 represents the baseline compression ignition (CI) mode combustion. At all rp, EGR rate and ICT were varied from 0 to 30% and 40° to 80°C, respectively.

Abstract The aim of this work is to quantify three different antioxidants in biodiesel - Santoflex, baynox, and tocopherol-using Middle Infrared (MIR) spectroscopy and chemometrics. For the construction of the models, 28 samples containing an antioxidant in the range of 0.1 to 500 mg/kg in biodiesel were used. We developed three models based on PLS 1 multivariate calibration method to quantify each of the three antioxidants separately and a model based on PLS 2 method to quantify simultaneously all the antioxidants. All models were compared to the values of root mean square error of calibration (RMSEC) and validation (RMSEP). For the baynox, santoflex, and tocopherol antioxidants quantification using PLS 1, the values of RMSEC and RMSEP were 37.2, 18.8, 9.0 mg/kg, and 26.7, 21.1, 68.6 mg/kg, respectively.