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The energy management strategy, commonly known as the EMS, is an essential component of fuel cell cars (FCVs). The majority of current research is concentrated on centralized emergency management systems (Cen-EMSs), but it does not provide sufficient flexibility (plug-and-play) or robustness. Regarding this matter, a hierarchical decentralized energy management system (Dec-EMS) that is based on a model predictive control (MPC) technique is offered for a modular FCV powertrain that is comprised of two parallel proton exchange membrane fuel cells (PEMFC) and an energy storage system. Gain scheduling makes the proposed Dec-EMS controller more effective in terms of its performance. The hierarchical decentralized control approach is assessed within the framework of a driving scenario that is representative of real-world conditions. According to the numerical result, the decentralized emergency management system (Dec-EMS) proposal provides superior performance than the centralized approach.

As a crucial part of the intelligent transportation system, traffic signal control will realize the boundary control of the traffic area, it will also lead to delays and excessive fuel consumption when the vehicle is driving at the intersection. To tackle this challenge, this research provides an optimized control framework based on reinforcement learning method and speed guidance strategy for the connected vehicle network. Prior to entering an intersection, vehicles are focused on in a specific speed guidance area, and important factors like uniform speed, acceleration, deceleration, and parking are optimized. Conclusion, derived from deep reinforcement learning algorithm, the summation of the length of the vehicle’s queue in front of the signal light and the sum of the number of brakes are used as the reward function, and the vehicle information at the intersection is collected in real time through the road detector on the road network.

To reduce the energy consumption level of electric vehicles, the working range of the regenerative braking system will gradually expand to the high state of charge of the battery. The time delay in the control signal transmission path of the high state of charge regenerative braking control process will affect the regenerative braking. At the same time, regenerative braking under a high state of charge puts forward higher requirements for the control accuracy of regenerative current. In the research of this paper, the motor model, battery model, and vehicle dynamics model are firstly established by using MATLAB/Simulink, and the dynamic relationship between regenerative current and regenerative braking torque is analyzed at the same time. Considering the system time delay, this paper proposes a high-charge regenerative braking control strategy (SPPC) that combines Smith prediction and prescribed performance control.

Due to traffic congestion and environmental pollution, connected automated vehicle (CAV) technologies based on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure communication (V2I) have gained increasing attention from both academia and industry. Connected hybrid electric vehicles (CHEVs) offer great opportunities to reduce vehicular operating costs and emissions. However, in complex traffic scenarios, high-quality real-time energy management of CHEVs remains a technical challenge. To address the challenge, this paper proposes a hierarchical eco-driving strategy that consists of speed planning and energy management layers. At the upper layer, by leveraging the real-time traffic data provided by vehicle-to-everything (V2X) communication, dynamic traffic constraints are predicted by the traffic flow predictor developed based on the Hankel dynamic mode decomposition algorithm (H-DMD).

Gasoline-related factors that affect low-speed pre-ignition (LSPI) include the distillation properties of gasoline, manganese (Mn), ethanol, diesel fuel, detergent for aftermarket, and iron (Fe). The combined effect of Mn with ethanol or high calcium engine oil (high-Ca oil) has not been sufficiently clarified. Therefore, appropriate countermeasures for LSPI have not yet been implemented. To clarify the effect of the gasoline properties and additives on LSPI, engine tests were conducted using gasoline with different “PM Index” values, an indicator of distillation properties, different concentrations of Mn, ethanol, diesel fuel, detergent, Fe, and high-Ca oil. The results showed that the LSPI frequency tended to increase with the PM Index, Mn up to 60 ppm, diesel fuel up to 2 vol.%, and detergent up to three times the standard amount.

Developing pure electric powertrains have become an important way to reduce reliance on crude oil in recent years. This paper concerns energy management of dual motor-driven electric vehicles. In order to obtain a predictive energy management strategy with good performance in computation and energy efficiency, we propose a hybrid algorithm that combines model predictive control (MPC) and convex programming to minimize electrical energy use in real time control. First, few changes are occurred in original component models in order to convert the original optimal control problem into convex programming problem. Then convex optimization algorithm is used in the prediction horizon to optimize torque allocation between two electric motors with different size. To verify the effectiveness of the hybrid algorithm, a real city driving cycle is simulated. Furthermore, different predictive horizons are performed to illustrate the robustness and time efficiency of the proposed method.

China's auto market has developed rapidly in recent years and has become the world's largest auto market. The rapid increase in sales of passenger cars has brought a series of environmental and energy problems. In response to these problems, “The Parallel Management Method for Corporate Average Fuel Consumption and New Energy Vehicles Credits” (Dual-credit Regulation) has been enacted in 2018. However, some problems about the regulation were gradually exposed with the NEV subsidies decreasing, such as too much surplus new energy vehicle credit. To promote the development of NEV, the reform of dual credit regulation was issued in June,2020.

HTL is a kind of biodiesel converted from wet biowaste via hydrothermal liquefaction (HTL), which has drawn increasing attention in recent years due to its wide range of raw materials (algae, swine manure, and food processing waste). However, from the previous experiments done in a constant volume chamber, it was observed that the presence of 20% of HTL in the blend produced as much soot as pure diesel at in chamber environment oxygen ratio of 21%, and even more soot at low oxygen ratios. It was also observed that n-butanol addition could reduce the soot emission of diesel significantly under all tested conditions. In this work, the spray and combustion characteristics of HTL and diesel blends with n-butanol added were investigated in a constant volume chamber. The in-chamber temperature and oxygen ranged from 800 to 1200 K and 21% to 13%, respectively, covering both conventional and low-temperature combustion (LTC) regimes.

The SAE J300 classification was expanded to 0W-12 and 0W-8 viscosity grades in 2015, and lower viscosity engine oils have been studied in the industry. ILSAC GF-6B that will be introduced in 2020 will specify a 0W-16 requirement, but 0W-12 and 0W-8 grades are not considered. Because engine oil equal to or higher than the 0W-20 grade is recommended for almost all engines globally, suitable engine tests for 0W-12 and 0W-8 do not exist. Therefore, the Japan Automobile Manufacturers Association, Petroleum Association of Japan and Society of Automotive Engineers of Japan decided to establish new 0W-12 and 0W-8 low viscosity engine oil specifications. It is referred to as JASO GLV-1, and together with a new fuel economy engine test procedure, these engine oils for better fuel economy will be put on the Japanese market in 2019. Motoring friction torque tests are widely used to ascertain the friction reduction effect of fuel-economy engine oils.

Flash boiling has drawn much attention recently for its ability to enhance spray atomization and vaporization, while providing better fuel/air mixing for gasoline direct injection engines. However, the behaviors of flash boiling spray with multi-component fuels have not been fully discovered. In this study, isooctane, ethanol and the mixtures of the two with three blend ratios were chosen as the fuels. Measurements were performed with constant fuel temperature while ambient pressures were varied to adjust the superheated degree. Macroscopic and microscopic characteristics of flash boiling spray were investigated using Diffused Back-Illumination (DBI) imaging and Phase Doppler Anemometry (PDA). Comparisons between flash boiling sprays with single component and binary fuel mixtures were performed to study the effect of fuel properties on spray structure as well as atomization and vaporization processes.

The spray structure and vaporization processes of flash-boiling sprays in a constant volume chamber under a wide range of superheated conditions were experimentally investigated by a high speed imaging technique. The Engine Combustion Network’s Spray G injector was used. Four fuels including gasoline, ethanol, and gasoline-ethanol blends E30 and E50 were investigated. Spray penetration length and spray width were correlated to the degree of the superheated degree, which is the ratio of the ambient pressure to saturated vapor pressure (pa/ps). It is found that parameter pa/ps is critical in describing the spray transformation under flash-boiling conditions. Three distinct stages namely the slight flash-boiling, the transition flash-boiling, and the flare flash-boiling are identified to describe the transformation of spray structures.

The performances of heavy-duty natural gas engines have been limited by combustion temperature and NOx emissions for a long time. Recently, water injection technology has been widely considered as a technical solution in reducing fuel consumption and emissions simultaneously in both gasoline and diesel engines. This paper focuses on the impacts of intake manifold water injection on characteristics of combustion and emissions in a natural gas heavy-duty engine through numerical methods. A computational model was setup and validated with experimental data of pressure traces in a CFD software coupled with detailed chemical kinetics. The simulation was mainly carried out in low-speed and full-load conditions, and knock level was also measured and calculated by maximum amplitude of pressure oscillations (MAPO).

Light-duty China-6, which is among the most stringent vehicle exhaust emission standards globally, mandates the monitoring and reporting of real driving emissions (RDE) from July, 2023. In the process of regulation promulgation and verification, more than 300 RDE tests have been performed on over 50 China-5 and China-6 certified models. This technical paper endeavors to summarize the experience of RDE practice in China, and discuss the impacts of some boundary conditions (including vehicle dynamic parameters, data processing methods, hybrid propulsion and testing altitude) on the result of RDE measurement. In general, gasoline passenger cars confront few challenges to meet the upcoming RDE NOx requirement, but some China-5 certified samples, even powered by naturally-aspirated engines may have PN issues. PN emissions from some GDI-hybrid powertrain systems also need further reduction to meet China-6 RDE requirements.

Particulate matter emissions are becoming a big issue for GDI engines as the emission regulations being more stringent. Methanol has been considered to be an important alternative fuel to reduce soot emissions. To understand the effect of methanol addition on soot and polycyclic aromatic hydrocarbons (PAHs) formation, the 2-D distributions of soot volume fraction and different size PAHs relative concentrations in methanol/gasoline laminar diffusion flames were measured by TC-LII and PLIF techniques. The effect of methanol was investigated under the conditions of the same carbon flow and the same flame height. The methanol volume fraction was set as M0/20/40/60/80. The results showed that the natural luminescent flame lift-off height and soot lift-off height increases consistently with the increasing methanol content due to the increase of outlet velocity of fuel vapor.

Methanol has been regarded as a potential transportation fuel due to its advanced combustion characteristics and flexible source. However, it is suffering from misfire and high HC emissions problems under cold start and low load conditions either on methanol SI engine or on methanol/diesel dual fuel engine. Hydrogen is a potential addition that can enhance the combustion of methanol due to its high flammability and combustion stability. In the current work, the effect of hydrogen fraction on the laminar flame characteristics of methanol- hydrogen-air mixture under varied equivalence ratio was investigated on a constant volume combustion chamber system coupled with a schlieren setup. Experiments were performed over a wide range of equivalence ratio of the premixed charge, varied from 0.8 to 1.4, as well as different hydrogen fraction, 0%, 5%, 10%, 15% and 20% (n/n). All tests were carried out at fixed temperature and pressure of 400K and 0.1MPa.

CNG-diesel dual fuel combustion mode has been regarded as a practical operation strategy because it not only can remain high thermal efficiency but also make full use of an alternative fuel, natural gas. However, it is suffering from misfire and high HC emissions under cold start and low load conditions. As known, hydrogen has high flammability. Thus, a certain proportion of hydrogen can be added in the natural gas (named HCNG) to improve combustion performance. In this work, the effect of hydrogen volume ratio on combustion characteristics was investigated on an optically accessible single-cylinder CNG-diesel engine using a Phantom v7.3 color camera. HCNG was compressed into the tank under different hydrogen volume ratios varied from 0% to 30%, while the energy substitution rate of` HCNG remained at 70%.

Bio-butanol has been widely investigated as a promising alternative fuel. However, the main issues preventing the industrial-scale production of butanol is its relatively low production efficiency and high cost of production. Acetone-butanol-ethanol (ABE), the intermediate product in the ABE fermentation process for producing bio-butanol, has attracted a lot of interest as an alternative fuel because it not only preserves the advantages of oxygenated fuels, but also lowers the cost of fuel recovery for individual component during fermentation. If ABE could be directly used for clean combustion, the separation costs would be eliminated which save an enormous amount of time and money in the production chain of bio-butanol.

Bio-butanol has been considered as a promising alternative fuel for internal combustion engines due to its advantageous physicochemical properties. However, the further development of bio-butanol is inhibited by its high recovery cost and low production efficiency. Hence, the goal of this study is to evaluate two upstream products from different fermentation processes of bio-butanol, namely acetone-butanol-ethanol (ABE) and isopropanol-butanol-ethanol (IBE), as alternative fuels for diesel. The experimental comparison is conducted on a single-cylinder and common-rail diesel engine under various main injection timings (MIT) and equivalent engine load (EEL) conditions. The experimental results show that ABE and IBE significantly affect the combustion phasing. The start of combustion (SOC) is retarded when ABE and IBE are mixed with diesel. Furthermore, the ABE/IBE-diesel blends are more sensitive to the changes in MIT compared with that of pure diesel.

Soot emission, known as PM (particulate matter), is becoming a big issue for GDI engines as the emission regulations being increasingly stricter. It is found that ethanol, as an oxygenated bio-fuel, can reduce the soot emission when added to gasoline. In order to fully understand the effect of ethanol on soot reducing, the soot characteristics of ethanol/gasoline blends were studied on laminar diffusion flames. In this experiment, the blending ratio of ethanol/gasoline was set as E0/20/40/60/80. Considering the carbon content decreasing due to ethanol addition, carbon mass flow rate was remained constant. The two-dimensional distributions of soot volume fraction were measured quantitatively by using two-color laser induced incandescence technique. The results showed that ethanol is able to decrease the soot significantly, but the effect of ethanol on soot reduction is weakened with the increasing ethanol ratio.

Considering the randomness and instability of the oil pressure in the lubrication system, a new approach for fault detection and diagnosis of diesel engine lubrication system based on support vector machine optimized by particle swarm optimization (PSO-SVM) model and centroid location algorithm has been proposed. Firstly, PSO algorithm is chosen to determine the optimum parameters of SVM, to avoid the blindness of choosing parameters. It can improve the prediction accuracy of the model. The results show that the classify accuracy of PSO-SVM is improved compared with SVM in which parameters are set according to experience. Then, the support vector machine classification interface is fitted to a curve, and the boundary conditions of fault diagnosis are obtained. Finally, diagnose algorithm is achieved through analyzing the centroid movement of features. According to Performance degradation data, degenerate trajectory model is established based on centroid location.