This paper proposes a double layered multi parameters braking energy recovery control strategy for Hybrid Electric Vehicle, which can combine the mechanical brake system with the motor brake system in the braking process to achieve higher energy utilization efficiency and at the same time ensure that the vehicle has sufficient braking performance and safety performance. The first layer of the control strategy proposed in this paper aims to improve the braking force distribution coefficient of the front axle. On the basis of following the principle of braking force distribution, the braking force of the front axle and the rear axle is reasonably distributed according to the braking strength. The second layer is to obtain the proportional coefficient of regenerative braking, considering the influence of vehicle speed, braking strength, and power battery state of charge (SOC) on the front axle mechanical braking force and motor braking force distribution, and a three-input single-output fuzzy controller is designed to realize the coordinated control of mechanical braking force and motor braking force of the front axle. Finally, the AMESim and Matlab/Simulink co-simulation model was built; the braking energy recovery control strategy proposed in this paper was simulated and analyzed based on standard cycle conditions (the NEDC and WLTC), and the simulation results were compared with regenerative braking control strategies A and B. The research results show that the braking energy recovery rate of the proposed control strategy is respectively 2.42%, 18.08% and 2.56%, 16.91% higher than that of the control strategies A and B, which significantly improves the energy recovery efficiency of the vehicle.

Steam methane reforming is a major method of hydrogen production. However, this method usually suffers from low energy efficiency and high carbon-emission intensity. To solve this issue, a novel steam-methane-reforming process over a Ni-based catalyst in a pressurized dual fluidized bed reactor is proposed in this work. A three-dimensional computational fluid dynamics (CFD) model for the complex physicochemical process was built to study the reforming characteristics. The model was first validated against the reported data in terms of hydrodynamics and reaction kinetics. Next, the performance of the proposed methane-steam-reforming process was predicted. It was found that the methane-conversion ratio was close to 100%. The mole fraction of H₂ in the dry-yield syngas reached 98.8%, the cold gas efficiency reached 98.5%, and the carbon-capture rate reached 96.4%. It is believed that the proposed method can be used for methane reforming with high efficiency and low carbon intensity.

This paper proposes a novel hybrid power system to improve the shift quality of a hybrid electric vehicle (HEV). After selecting a typical shift scheme, the study focused on the motor rotary velocity control algorithm and coordinated control strategy for the motor and clutch. The effects of various control algorithms on different target rotary velocities were analyzed, and a proportional-integral-derivative (PID)–bang-bang–fuzzy compound intelligent algorithm for a motor rotary velocity control system was investigated. In addition, to address the problems of the long synchronizing time required for the rotary velocity and large sliding friction work, which affect the shift quality during the process of engaging the clutch, a coordinated control strategy for the motor rotary velocity and clutch oil pressure was investigated. The research results showed that, compared with a gear shift coordinated control strategy based on a PID control algorithm, the strategy based on the PID–bang-bang–fuzzy compound intelligent control algorithm proposed here reduced the shift time and clutch slipping friction work by 35.7% and 19.2%, respectively.

The combined cooling, heating, and power (CCHP) system has attracted increasing attention due to its potential outstanding performance in thermodynamics, economics, and the environment. However, the conventional CCHP systems are carbon-intensive. To solve this issue, a low-carbon-emission CCHP system (LC-CCHP) is firstly proposed in this work by integrating a sorption-enhanced steam methane reforming (SE-SMR) process. In the LC-CCHP system, CO₂ is continuously captured by the calcium loop so that low-carbon energy can be generated. Then, the LC-CCHP system thermodynamic model, mainly consisting of a dual fluidized bed reactor which includes the SE-SMR reactor and a CaCO₃ calcination reactor, a hydrogen gas turbine, a CO₂ reheater, and a lithium bromide absorption chiller, is built. To prove that the LC-CCHP model is reliable, the system major sub-unit model predictions are compared against data from the literature in terms of thermodynamics and economics. Finally, the effects of reforming temperature (T_ref), the steam-to-carbon mole ratio (S/C), the calcium-to-carbon mole ratio (R_CC), the equivalent ratio for gas turbine (R_AE), and the hydrogen separation ratio (S_fg) on total energy efficiency (${\eta }_{ten}$), total exergy efficiency (${\eta }_{tex}$), and carbon capture capability ($R_{cm}$) are detected. It is found that the minimum exergy efficiency of 64.5% exists at the calciner unit, while the maximum exergy efficiency of 78.7% appears at the gas turbine unit. The maximum energy efficiency and coefficient of performance of the absorption chiller are 0.52 and 1.33, respectively. When $T_{ref}=600$ °C, $S/C=4.0$, $R_{CC}=7.62$, $R_{AE}=1.20,$ and $S_{fg}=0.27$, the ${\eta }_{ten}$, ${\eta }_{tex,}$ and $R_{cm}$ of the system can be ~61%, ~68%, and ~96%, and the average specific cost of the system is 0.024 USD/kWh, which is advanced compared with the parallel CCHP systems.

Fixed bed reactors play an important role in converting solid wastes to high-quality products. The solid wastes, as well as the corresponding catalysts, are often made into cylindrical particles. However, research on the drag force for cylindrical particles is still rarely reported. In this work, the fixed bed porosity was firstly predicted with the unresolved CFD-DEM method and validated against experimental data. Then, the Ergun model, Di Felice model, and Ganser model were evaluated against the reported pressure drop data for both the spherical and cylindrical particles, so that a more solid drag force theory could be selected as a candidate for cylindrical particles. Finally, a new Ganser model was proposed for cylindrical particle drag force prediction based on the reported experimental results and validated by other experimental data. It was found that, for the spherical particle bed, the relative prediction errors of the Di Felice model are approximately 10%, while those of the Ergun model are approximately 15%. For the cylindrical particle bed, the relative prediction errors of the Ganser model are approximately 10%, while those of the Di Felice model are much higher than 10%. With the new Ganser model proposed in this work, the maximum error between the predicted pressure drop and the experimental data can be lowered to approximately 5%. The research is of reference value for drag force model selection when simulating similar FBRs with cylindrical particles.