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The absence of combustion information continues to be one of the key obstacles to the intelligent development of engines. Currently, the cost of integrating cylinder pressure sensors remains too high, prompting attention to methods for extracting combustion information from existing sensing data. Mean-value combustion models for engines are unable to capture changes of combustion parameters. Furthermore, the methods of reconstructing combustion information using sensor signals mainly depend on the working state of the sensors, and the reliability of reconstructed values is directly influenced by sensor malfunctions. Due to the concentration of operating conditions of hybrid vehicles, the reliability of priori calibration map has increased. Therefore, a combustion information reconstruction method based on priori calibration information and the fused feature deviations of existing sensing signals is proposed and named the "Deviation-based Centroid Displacement Method" (DCDM).

Parking-slot detection plays a critical role in the self-parking system for autonomous driving. To enhance the complexity of the environmental situations in parking-slot datasets and reduce the difficulty of manual annotation, we design several data synthesis methods to generate new parking-slots under different situations. Methods introduced in this paper include synthesizing parking-slots in AVM (around view monitor) images, generating parking-slots in fisheye images and adding 2D symbols inside parking-slots to form special ones. To test the influence of our synthetic data, we conduct a series of experiments on different tasks. In the parking-slot detection experiments, we design a novel two-stage parking-slot detection method. We use YOLOv7 as the object detector and different from previous methods, we detect the complete parking-slots and marking points at the same time. Then we match marking points and give them a certain order in the second stage.

The development of autonomous driving generally requires enormous annotated data as training input. The availability and quality of annotated data have been major restrictions in industry. Data synthesis techniques are then being developed to generate annotated data. This paper proposes a 2D data synthesis pipeline using original background images and target templates to synthesize labeled data for model training in autonomous driving. The main steps include: acquiring templates from template libraries or alternative approaches, augmenting the obtained templates with diverse techniques, determining the positioning of templates in images, fusing templates with background images to synthesize data, and finally employing the synthetic data for subsequent detection and segmentation tasks. Specially, this paper synthesizes traffic data such as traffic signs, traffic lights, and ground arrow markings in 2D scenes based on the pipeline.

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.

The automobile industry is under intense pressure to reduce carbon dioxide (CO2) emissions of vehicles. There is also increasing pressure to reduce the other tail-pipe emissions from vehicles to combat air pollution. Electric powertrains offer great potential for eliminating tailpipe CO2 and all other tailpipe emissions. However, current battery technology and recharging infrastructure still present limitations for some applications, where a continuous high-power demand is required. Furthermore, not all markets have the infrastructure to support a sizeable electric fleet and until the grid energy generation mix is of a sufficiently low carbon intensity, then significant vehicle life-cycle CO2 savings could not be realized by the Battery Electric Vehicles. This investigation examines the effects of combustion, efficiencies, and emissions of two alcohol fuels that could help to significantly reduce CO2 in both tailpipe and the whole life cycle.

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.

With the rapid development of autonomous driving technologies, the proportion of autonomous vehicles (AVs) will increase and influence road capacity. In this study, the simulation of mixed traffic flow was studied using an improved cellular automata model. Safety inter-vehicle spacing, the length of vehicles and reaction time are introduced into the cellular automata model. We delete the acceleration, deceleration and randomization rule for ideal conditions. Numerical simulations are utilized to analyze road capacity with different proportions of AVs. Road capacity is about 2200 pcu/h/lane for pure manual vehicle (MV) traffic flow and about 3600 pcu/h/lane for pure AV traffic flow. The capacity increases by 19.2% when there are 50% AVs in the traffic flow. And the capacity increases by around 63.6% due to the pure AV traffic flow.

Engine downsizing is an effective technology to lower automotive CO2 emissions. However, the high load low speed regions are plagued with knocking combustion that are usually overcome by retarding the ignition. This interferes with the efficiency gains due to very late combustion. This paper reports the use of Exhaust Gas Recirculation (EGR) on a Ford Ecoboost 1l downsized gasoline turbocharged direct injection (GTDI) engine to improve efficiency by optimising combustion phasing unlocked by the improved knock resistance with EGR dilution. Further ignition system upgrades are tested for impact towards further efficiency improvements. 75mJ (standard) and 120mJ (high energy) ignition systems were compared. The experimental results showed that the brake specific fuel consumption (BSFC) can be improved by 5.6% with EGR dilution at 25%. When considering combined effects of EGR and high energy ignition upon engine fuel economy, the BSFC gain improves to 7.9%.

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.

One promising method for reducing fuel consumption and emissions, particularly in heavy duty trucks, is platooning. As the distance between vehicles decreases, the following vehicles will experience less aerodynamic drag on the front of the vehicle. However, reducing the velocity of the air contacting the front of the vehicle could have adverse effects on the temperature of the engine. To compensate for this effect, the energy consumption of the engine cooling system might increase, ultimately limiting the overall improvements obtained with platooning. Understanding the coupling between drag reduction and engine cooling load requirement is key for successfully implementing platooning strategies. Additionally, in a Connected and Automated Vehicle (CAV) environment, where information of the future engine load becomes available, the operation of the cooling system can be optimized in order to achieve the maximum fuel consumption reduction.

Engine downsizing is one of the most effective means to improve the fuel economy of spark ignition (SI) gasoline engines because of lower pumping and friction losses. However, the occurrence of knocking combustion or even low-speed pre-ignition at high loads is a severe problem. One solution to significantly increase the upper load range of a 4-stroke gasoline engine is to use 2-stroke cycle due to the double firing frequency at the same engine speed. It was found that a 0.7 L two-cylinder 2-stroke poppet valve gasoline engine equipped with a two-stage serial boosting system, comprising a supercharger and a downstream turbocharger, could replace a 1.6 L naturally aspirated 4-stroke gasoline engine in our previous research, but its fuel economy was close to that of the 4-stroke engine at upper loads due to knocking combustion.

In order to meet increasingly stringent emissions standards and lower the fuel consumption of heavy-duty (HD) vehicles, significant efforts have been made to develop high efficiency and clean diesel engines and aftertreatment systems. However, a trade-off between the actual engine efficiency and nitrogen oxides (NOx) emission remains to minimize the operational costs. In addition, the conversion efficiency of the diesel aftertreatment system decreases rapidly with lower exhaust gas temperatures (EGT), which occurs at low load operations. Thus, it is necessary to investigate the optimum combustion and engine control strategies that can lower the vehicle’s running costs by maintaining low engine-out NOx emissions while increasing the conversion efficiency of the NOx aftertreament system through higher EGTs.

This paper describes a novel design and verification process for analytical methods used in the development of advanced combustion strategies in internal combustion engines (ICE). The objective was to improve brake thermal efficiency (BTE) as part of the US Department of Energy SuperTruck program. The tools and methods herein discussed consider spray formation and injection schedule along with piston bowl design to optimize combustion efficiency, air utilization, heat transfer, emission, and BTE. The methodology uses a suite of tools to optimize engine performance, including 1D engine simulation, high-fidelity CFD, and lab-scale fluid mechanic experiments. First, a wide range of engine operating conditions are analyzed using 1-D engine simulations in GT Power to thoroughly define a baseline for the chosen advanced engine concept; secondly, an optimization and down-select step is completed where further improvements in engine geometries and spray configurations are considered.

Modern heavy duty diesel engines can well extend the goal of 50% brake thermal efficiency by utilizing waste heat recovery (WHR) technologies. The effect of an ORC WHR system on engine brake specific fuel consumption (bsfc) is a compromise between the fuel penalty due to the higher exhaust backpressure and the additional power from the WHR system that is not attributed to fuel consumption. This work focuses on the fuel efficiency benefits of installing an ORC WHR system on a heavy duty diesel engine. A six cylinder, 7.25ℓ heavy duty diesel engine is employed to experimentally explore the effect of backpressure on fuel consumption. A zero-dimensional, detailed physical ORC model is utilized to predict ORC performance under design and off-design conditions.

As the emission regulations for internal combustion engines are becoming increasingly stringent, different solutions have been researched and developed, such as dual injection systems (combined port and direct fuel injection), split injection strategies (single and multiple direct fuel injection) and different intake air devices to generate an intense in-cylinder air motion. The aim of these systems is to improve the in-cylinder mixture preparation (in terms of homogeneity and temperature) and therefore enhance the combustion, which ultimately increases thermal efficiency and fuel economy while lowering the emissions. This paper describes the effects of dual injection systems on combustion, efficiency and emissions of a downsized single cylinder gasoline direct injection spark ignited (DISI) engine. A set of experiments has been conducted with combined port fuel and late direct fuel injection strategy in order to improve the combustion process.

Engine downsizing can effectively improve the fuel economy of spark ignition (SI) gasoline engines, but extreme downsizing is limited by knocking combustion and low-speed pre-ignition at higher loads. A 2-stroke SI engine can produce higher upper load compared to its naturally aspirated 4-stroke counterpart with the same displacement due to the double firing frequency at the same engine speed. To determine the potential of a downsized two-cylinder 2-stroke poppet valve SI gasoline engine with 0.7 L displacement in place of a naturally aspirated 1.6 L gasoline (NA4SG) engine, one-dimensional models for the 2-stroke gasoline engine with a single turbocharger and a two-stage supercharger-turbocharger boosting system were set up and validated by experimental results.

Engine downsizing of the spark ignition gasoline engine is recognized as one of the most effective approaches to improve the fuel economy of a passenger car. However, further engine downsizing beyond 50% in a 4-stroke gasoline engine is limited by the occurrence of abnormal combustion events as well as much greater thermal and mechanical loads. In order to achieve aggressive engine downsizing, a boosted uniflow scavenged direct injection gasoline (BUSDIG) engine concept has been proposed and researched by means of CFD simulation and demonstration in a single cylinder engine. In this paper, the intake port design on the in-cylinder flow field and gas exchange characteristics of the uniflow 2-stroke cycle was investigated by computational fluid dynamics (CFD). In particular, the port orientation on the in-cylinder swirl, the trapping efficiency, charging efficiency and scavenging efficiency was analyzed in details.

An experimental study has been carried out with the end goal of minimizing engine-out methane emissions with Premixed Micro Pilot Combustion (PMPC) in a natural gas-diesel Dual-Fuel™ engine. The test engine used is a heavy-duty single cylinder engine with high pressure common rail diesel injection as well as port fuel injection of natural gas. Multiple variables were examined, including injection timings, exhaust gas recirculation (EGR) percentages, and rail pressure for diesel, conventional Dual-Fuel, and PMPC Dual-Fuel combustion modes. The responses investigated were pressure rise rate, engine-out emissions, heat release and indicated specific fuel consumption. PMPC reduces methane slip when compared to conventional Dual-Fuel and improves emissions and fuel efficiency at the expense of higher cylinder pressure.

The work was concerned with experimental study of the turbulent flame development process of ethanol fuels in an optically accessed spark ignition research engine. The fuels were evaluated in a single cylinder engine equipped with full-bore overhead optical access and operated at typical stoichiometric part-load conditions. High-speed natural light (or chemiluminescence) imaging and simultaneous in-cylinder pressure data measurement and analysis were used to understand the fundamental influence of both low and high ethanol content on turbulent flame propagation and subsequent mass burning. Causes for the difference in cyclic variations were evaluated in detail, with comparisons made to existing burning velocity correlations where available.