Optimizing traffic control systems at traffic intersections can reduce network-wide fuel consumption as well as improve traffic flow. While traffic signals have conventionally been controlled based on predetermined schedules, various adaptive control systems have been developed recently using advanced sensors such as cameras, radars, and LiDARs. By utilizing rich traffic information enabled by the advanced sensors, more efficient or optimal traffic signal control is possible in response to varying traffic conditions. This paper proposes an optimal traffic signal control method to minimize network-wide fuel consumption utilizing real-time traffic information provided by advanced sensors. This new method employs a priority metric calculated by a weighted sum of various factors, including the total number of vehicles, total vehicle speed, vehicle waiting time, and road preference. Genetic Algorithm (GA) is used as a global optimization method to determine the optimal weights in the priority metric. In order to evaluate the effectiveness of the proposed method, a traffic simulation model is developed in a high-fidelity traffic simulation environment called SUMO, based on a real-world traffic network. The traffic flow within this model is simulated using actual measured traffic data from the traffic network, enabling a comprehensive assessment of the novel optimal traffic signal control method in realistic conditions. The simulation results show that the proposed priority metric-based real-time traffic signal control algorithm can significantly reduce network-wide fuel consumption compared to the conventional fixed-time control and coordinated actuated control methods that are currently used in the modeled network. Additionally, incorporating truck priority in the priority metric leads to further improvements in fuel consumption reduction.

Due to its ease of use in diesel engines, its presumably lower carbon footprint, and its potential as a renewable fuel, biodiesel has attracted considerable attention in technological development and research literature. Much literature is devoted to evaluating the injection and combustion characteristics of biodiesel fuel using unit injectors, where injection pressure and timing are regulated within the same unit. The use of common rail fuel systems, where fuel pressure is now equally governed to each injector (of a multi-cylinder engine), may change the conventionally accepted impact of biodiesel on injection and combustion characteristics. The objectives of this study are to characterize the responses of an electronically-controlled common-rail fuel injector (in terms of timing and duration) when delivering either 100% palm olein biodiesel or 100% petroleum diesel for a diesel engine, and correlate potential changes in injector characteristics to changes in combustion. The experimental study relies on the analysis of injector command and needle lift measurements to identify major differences (or indifferences) of injection characteristics of biodiesel fuel (relative to petroleum diesel fuel). Further, in-cylinder pressure measurements provide the basis for apparent heat release rate analysis in identifying critical combustion characteristics (i.e., ignition delay and combustion duration). Differing from the typically-observed artificial advance in injection timing with bio-diesel, this study finds that there are no observable differences in the injection timing or needle lift behavior with biodiesel (relative to petroleum diesel) in a common rail diesel engine.

Cylinder-to-cylinder variation in a multi-cylinder diesel engine was found to increase substantially when transitioning to a low-temperature combustion mode. This study was started to investigate the potential influence this effect could have on the emissions levels. Initial testing showed an imbalance in the fuel distribution that prompted this article to focus on data from before and after swapping two injectors under both conventional and low-temperature combustion modes. A significant improvement is observed in cylinder variation based both on visual heat release inspection and on mean effective pressure variation. This is likely a result of a changing combination of exhaust gas recirculation and fuel distribution such that less cylinder-to-cylinder variation is present (e.g. high dilution and low fuel, switched to low dilution and low fuel). Interestingly, despite the reduced cylinder-to-cylinder variation, the results show that the emissions levels are actually not affected. Despite the lack of influence on emissions results, the cylinder-to-cylinder variation in low-temperature combustion modes is still a critical factor that could impact its ability to be implemented in a commercial setting. Further cylinder balancing was attempted and achieved by introducing small (microsecond) adjustments to each cylinder start of injection and injection duration. The balancing is effective, but due to exhaust gas recirculation imbalance, a single adjustment setting does not apply to both conventional and low-temperature combustion modes. Additionally, day-to-day ambient conditions also negate the effectiveness. This supports the idea that some type of consumer-based real-time automatic balancing system may be needed in the future.