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The environmental and sustainable energy concerns in transport are being addressed through the decarbonisation path and the potential of hydrogen as a zero-carbon alternative fuel. Using hydrogen to replace fossil fuels in various internal combustion engines shows promise in enhancing efficiency and achieving carbon-neutral outcomes. This study presents an experimental investigation of hydrogen (H2) combustion and engine performance in a boosted spark ignition (SI) engine. The H2 engine incorporates both port fuel injection (PFI) and direct injection (DI) hydrogen fuel systems, capable of injecting hydrogen at pressures of up to 4000 kPa in the DI system and 1000 kPa in the PFI operations. This setup enables a direct comparison of the performance and emissions of the PFI and DI operations. The study involves varying the relative air-to-hydrogen ratio (λ) at different speeds to explore combustion and engine limits for categorising and optimising operational regions.

The China Automotive Technology and Research Center (CATARC) has completed two new wind tunnels at its test centre in Tianjin, China: an aerodynamic/aeroacoustic wind tunnel (AAWT), and a climatic wind tunnel (CWT). The AAWT incorporates design features to provide both a very low fan power requirement and a very low background noise putting it amongst the quietest in the automotive world. These features are also combined with high flow quality, a full boundary layer control system with a 5-belt rolling road, an automated traversing system, and a complete acoustic measurement system including a 3-sided microphone array. The CWT, located in the same building as the AAWT, has a flexible nozzle to deliver 250 km/h with an 8.25 m2 nozzle, and 130 km/h with a 13.2 m2 nozzle. The temperature range of the CWT is -40 °C to +60 °C with a controlled humidity range of 5% to 95%. Additional integrated systems include a variable angle solar simulator array, and a rain and snow spray system.

Climate change mitigation is the main challenge for the automotive industry, as the government issues legislation to combat CO2 emissions. In addition to electrification and battery electric vehicles, using low-carbon and zero-carbon fuels in Internal Combustion (IC) engines can also be an effective way to reach net zero-carbon transport. This study investigated and compared the combustion characteristics, performance and emissions of a highly boosted spark ignition (SI) engine fuelled with EU VI 95 RON E10 gasoline and blends of second-generation bio-gasoline with different ethanol contents of 5% (E5), 10% (E10), and 20% (E20). The single-cylinder SI engine was equipped with a centrally mounted high-pressure injector and supplied externally boosted air. Engine experiments were conducted at 2000 RPM and 3000 RPM with low and high load operations.

With the continuous development of the electrical vehicles (EVs), the electric power network and transportation network are interconnected by EVs which require a coordinated operation of the two networks. In view of these coupled networks, this paper proposes a charging navigation strategy for EVs based on charging power adjustment, which can not only provide the navigation path with the shortest total operational time for EVs from the origin node to the completion of charging, but also effectively reduce load fluctuations in the electric power system. In the electric power system, an innovative optimization strategy for adjusting the EV charging power distribution is proposed, which can adjust the charging power in a timely and effective manner according to the response of EV charging. The multi-objective particle swarm optimization (MOPSO) algorithm and the improved Dijkstra algorithm are used for solving the obtained the EV charging power adjustment plan and charging paths.

Fuel cell reactors, as the core components of fuel cell vehicles, have a short life problem that has always limited the development of fuel cell vehicles. The life attenuation curve of fuel cell shows nonlinear characteristics, and there is no model that can accurately predict its effect. This paper is based on the experimental data of the vehicle fuel cell reactor, which is derived from the 600 h durability test run by a 4 kW fuel cell reactor. The relevance vector machine, as a Bayes processing method that supports vector machine, is a data-driven method based on kernel functions. The regression model is established by the relevance vector machine, and the super-parameters are found by genetic algorithm, because the kernel function strongly affects the nonlinearity of the curve, and the decay curve of fuel cell reactor performance is predicted according to four different kernel functions.

In this study, a new system of assessment method was developed to evaluate the characteristics of urban buses based on remote online monitoring. Four types of buses, including China V emission standards diesel bus, lean-burn CNG bus, air-fuel equivalence ratio combustion CNG bus and gas-electric hybrid bus, were chosen as samples to analyze the emission characteristics of urban buses with different engine types in urban scenario. Based on the traffic conditions in Beijing, the actual emission characteristics of buses under newly-built driving conditions were analyzed. Moreover, the emission factor database of urban buses in Beijing was established to analyze the characteristics of excess emission. The research results are shown as follows. 1) Compared with other types of buses, NOX emission factor and emission rate of lean-burn CNG bus are much higher.

An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy.

Pumping Mean Effective Pressure (PMEP) is the main factor limiting the improvement of thermal efficiency in a spark-ignition (SI) engine under low load. One of the ways to reduce the pumping loss under low load is to use Cylinder DeActivation (CDA). The CDA aims at reducing the firing density (FD) of the SI engine under low load operation and increasing the mass of air-fuel mixture within one cycle in one cylinder to reduce the throttling effect and further reducing the PMEP. The multi-stroke cycles can also reduce the firing density of the SI engine after some certain reasonable design, which is feasible to improve the thermal efficiency of the engine under low load in theory. The research was carried out on a calibrated four-cylinder SI engine simulation platform. The thermal efficiency improvements of the 6-stroke cycle and 8-stroke cycle to the engine performance were studied compared with the traditional 4-stroke cycle under low load conditions.

Life prediction is a major focus for a commercial fuel cell stack, especially applied in fuel cell electric vehicles (FCEV). This paper proposes a data driven fuel cell lifetime prediction model using particle swarm optimized back-propagation neural network (PSO-BPNN). For the prediction model PSO-BP, PSO algorithm is used to determine the optimal hyper parameters of BP neural network. In this paper, total voltage of fuel cell stack is employed to represent the health index of fuel cell. Then the proposed prediction model is validated by the aging data from PEMFC stack in FCEV at the actual road condition. The experimental results indicate that PSO-BP model can predict the voltage degradation of PEMFC stack at actual road condition precisely and has a higher prediction accuracy than BP model.

Due to the rapid development of road infrastructure and vehicle population in China, the fuel consumption and emission of on-road vehicles tested in China World Transient Vehicle Cycle (C-WTVC) cannot indicate the real driving results. But the test results in China Heavy-duty Commercial Vehicle Test Cycle-Coach (CHTC-C) based on the road driving conditions in China are closer to the actual driving data. In this paper, the model for predicting the performance of heavy-duty vehicles is established and validated. The fuel consumption and NOx emission of a Euro VI heavy-duty coach under C-WTVC and CHTC-C tests are calculated by employing the developed model. Furthermore, the fuel consumption of the test coach is optimized and its sensitivity to the driving factors is analyzed.

Lean-burn combustion is an effective method for increasing the thermal efficiency of gasoline engines fueled with stoichiometric fuel-air mixture, but leads to an unacceptable level of high cyclic variability before reaching ultra-low nitrogen oxide (NOx) emissions emitted from conventional gasoline engines. Multi-point micro-flame ignited (MFI) hybrid combustion was proposed to overcome this problem, and can be can be grouped into double-peak type, ramp type and trapezoid type with very low frequency of appearance. This research investigates the micro-flame ignition stages of double-peak type and ramp type MFI combustion captured by high speed photography. The results show that large flame is formed by the fast propagation of multi-point flame occurring in the central zone of the cylinder in the double-peak type. However, the multiple flame sites occur around the cylinder, and then gradually propagate and form a large flame accelerated by the independent small flame in the ramp type.

Controlled Auto-Ignition (CAI) combustion can effectively improve the thermal efficiency of conventional spark ignition (SI) gasoline engines, due to shortened combustion processes caused by multi-point auto-ignition. However, its commercial application is limited by the difficulties in controlling ignition timing and violent heat release process at high loads. Stratified flame ignited (SFI) hybrid combustion, a concept in which rich mixture around spark plug is consumed by flame propagation after spark ignition and the unburned lean mixture closing to cylinder wall auto-ignites in the increasing in-cylinder temperature during flame propagation, was proposed to overcome these challenges.

Low combustion efficiency and high hydrocarbon emissions at low loads are key issues of natural gas and diesel (NG-diesel) dual fuel engines. For better engine performance, two diesel-spray-orientated (DSO) bowls were developed based on the existing diesel injector of a heavy-duty diesel engine with the purpose of placing more combustible natural gas/air mixture around the diesel spray jets. A protrusion-ring was designed at the rim of the piston bowl to enhance the in-cylinder flame propagation. Numerical simulations were conducted for a whole engine cycle at engine speed of 1200 r/min and indicated mean effective pressure (IMEP) of 0.6 MPa. Extended coherent flame model 3 zones (ECFM-3Z) combustion model with built-in soot emissions model was employed. Simulation results of the original piston bowl agreed well with the experimental data, including in-cylinder pressure and heat released rate (HRR), as well as soot and methane emissions.

The Gasoline direct-injection (GDI) engine can emit high levels of particulate matter and unburned Hydrocarbons when operating under stratified charge combustion mode. Injecting late in the compression stroke means the fuel has insufficient time to atomise and evaporate. This could cause fuel film accumulation on the piston surface and combustion liner. Locally fuel rich diffusion combustion could also result in the formation of soot particles. Employing a split-injection strategy can help tackle these issues. The first injection is initiated early in the intake stroke and could ensure a global homogeneous charge. The second injection during the compression stroke could help form a fuel-rich charge in the vicinity of the spark plug. Many studies have established the crucial role that a split-injection strategy plays in the stratified charge operation of GDI engines.

Controllability of ignition timing and combustion phase by means of dual-fuel direct injection strategy in jet-controlled compression ignition mode were investigated in a light-duty prototype diesel engine. Blended fuel with lower reactivity was delivered in the early period of compression stroke to form the premixed charge, while diesel fuel which has higher reactivity was injected near TDC to trigger the ignition. The effects of several important injection parameters including pre-injection timing, jet-injection timing, pre- injection pressure and ratio of pre-injection in the total heat value of injected fuel were discussed. Numerical Simulation by using CFD software was also conducted under similar operating conditions. The experimental results indicate that the jet-injection timing shows robust controllability on the start of combustion under all the engine load conditions.

Engine downsizing has established itself as one of the most successful strategies to reduce fuel consumption and pollutant emissions in the automotive field. To this regard, a major role is played by turbocharging, which allows an increase in engine power density, so reducing engine size and weight. However, the need for turbocharging imposes some issues to be solved. In the attempt of mitigating turbo lag and poor low-end torque, many solutions have been presented in the open literature so far, such as: low inertia turbine wheels and variable geometry turbines; or even more complex concepts such as twin turbo and electrically assisted turbochargers. None of them appears as definitive, though. As a possible way of reducing turbine rotor inertia, and so the turbo lag, also the change of turbine layout has been investigated, and it revealed itself to be a viable option, leading to the use of mixed-flow turbines.

Turbulent Jet Ignition (TJI) is a pre-chamber ignition system for an otherwise standard gasoline spark ignition engine. TJI works by injecting chemically active turbulent jets to initiate combustion in a premixed fuel/air mixture. The main advantage of TJI is its ability to ignite and burn, completely, very lean fuel/air mixtures in the main chamber charge. This occurs with a very fast burn rate due to the widely distributed ignition sites that consume the main charge rapidly. Rapid combustion of lean mixtures leads to lower exhaust emissions due to more complete combustion at a lower temperature. For this research, the effectiveness of the Mahle TJI system on combustion stability, lean limit and emissions in a single cylinder spark engine fueled with gasoline at different speeds was investigated. The combustion and heat release process was analyzed and the exhaust emissions were measured.

This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.

Controlled Auto-Ignition (CAI) combustion, also known as Homogeneous Charge Compression Ignition (HCCI), has the potential to simultaneously reduce the fuel consumption and nitrogen oxides emissions of gasoline engines. However, narrow operating region in loads and speeds is one of the challenges for the commercial application of CAI combustion to gasoline engines. Therefore, the extension of loads and speeds is an important prerequisite for the commercial application of CAI combustion. The effect of intake charge boosting, charge stratification and spark-assisted ignition on the operating range in CAI mode was reviewed. Stratified flame ignited (SFI) hybrid combustion is one form to achieve CAI combustion under the conditions of highly diluted mixture caused by the flame in the stratified mixture with the help of spark plug.

Controlled Auto-Ignition (CAI), also known as Homogeneous Charge Compression Ignition (HCCI), can improve the fuel economy of gasoline engines and simultaneously achieve ultra-low NOx emissions. However, the difficulty in combustion phasing control and violent combustion at high loads limit the commercial application of CAI combustion. To overcome these problems, stratified mixture, which is rich around the central spark plug and lean around the cylinder wall, is formed through port fuel injection and direct injection of gasoline. In this condition, rich mixture is consumed by flame propagation after spark ignition, while the unburned lean mixture auto-ignites due to the increased in-cylinder temperature during flame propagation, i.e., stratified flame ignited (SFI) hybrid combustion.