Public awareness regarding pollutants and their adverse health effects has created an urgent need for engineers to better understand the combustion process as well as the pollutants formed as by-products of that process. To effectively contribute to emission control strategies and design and develop emission control systems and components, a good understanding of the physical and mathematical principles of the combustion process is necessary. This seminar will bring issues related to combustion and emissions "down to earth," relying less on mathematical terms and more on physical explanations and analogies.
Connected and automated vehicles (CAVs) provide the most intriguing opportunity to reduce energy consumption and travel delays. In this paper, we propose a two-level control architecture for CAVs to optimize (1) the vehicle's speed profile, aimed at minimizing stop-and-go driving, and (2) the powertrain efficiency of the vehicle for the optimal speed profile derived in (1). The proposed hierarchical control framework can be implemented onboard the vehicle in real time with minimal computational effort. We evaluate the effectiveness of the efficiency of the proposed architecture through simulation in Mcity using a 100% penetration rate of CAVs. The results show that the proposed approach yields significant benefits both in energy and travel time.
In the development of an Adaptive Cruise Control (ACC) system, a model-based design process uses a simulation environment with models for sensor data, sensor fusion, ACC, and vehicle dynamics. Previous work has sought to control the dynamics between two vehicles both in simulation and in empirical testing environments. This paper outlines a new modular simulation framework for full model-based design integration, to iteratively design ACC systems. The simulation framework uses physics-based vehicle models to test ACC systems in three ways. The first two are Model-in-the-Loop (MIL) testing, using scripted scenarios or Driver-in-the-Loop (DIL) control of a target vehicle. The third testing method uses collected test data replayed as inputs to the simulation to additionally test sensor fusion algorithms. The simulation framework uses 3D visualization of the vehicles and implements mathematical driver comfortability models to better understand the perspectives of the driver or passenger.
2020 SAE Congress - Technical Paper Abstract "Smart Solutions for Electric Vehicle Suspensions" Session: Steering, Chassis and Suspension Authors: Peter Kuhn, SGL Technologies GmbH, Meitingen, Germany William D. Pinch, SGL Technologies LLC, Charlotte, NC USA Abstract: Battery Electric Vehicles (BEVs) Programs are becoming the vehicle of choice globally. This is driven by heightened vehicle emissions requirements and improved fuel economy performance. Vehicle requirements will be rolled down to Subsystems and Components. Subsystem requirements will be divided into upper and lower control planes with Kinematic performance targets discussed. Various types of front and rear suspensions will be identified and analyzed including MacPherson & Chapman Strut, Short-Long Arm (SLA), and various Multi-link arrangements. At the component level the use of innovative, lightweight composite materials provides a significant advantage.
Butanol, a four-carbon alcohol, is considered in the last years as an interesting alternative fuel, both for Diesel and for Gasoline application. Its advantages for engine operation are: good miscibility with gasoline and diesel fuels, higher calorific value than Ethanol, lower hygroscopicity, lower corrosivity and possibility of replacing aviation fuels. Like Ethanol, Butanol can be produced as a biomass-based renewable fuel or from fossil sources. In the research project, DiBut (Diesel and Butanol) addition of Butanol to Diesel fuel was investigated from the points of view of engine combustion and of influences on exhaust aftertreatment systems and emissions. One investigated engine (E1) was with emission class “EU Stage 3A” for construction machines, another one, engine (E2) was HD Euro VI. The operation of engine (E1) with Bu30 was instable at lower part load due to the lower Cetane Number of the blend fuel.
Regenerative braking in hybrid electric vehicles is a critical feature to achieve the maximum fuel economy benefit of hybridization. In order to maximize energy recuperation, it is desired to enable regenerative braking during an Anti-lock Braking System (ABS) event. For certain driveline configurations with a single electric motor connected to the axle shaft through an open differential, it has been observed that the regenerative braking torque can increase the wheel slip during the ABS operation, and significantly impact vehicle dynamics. This negative effect introduced by regen braking during ABS control may also lead to hardware failures, such as breaking a drive shaft. This paper describes development of an integrated regenerative braking and ABS control for hybrid and electric drive vehicles, referred to as RBS-ABS Event Control. This control is intended for drivelines containing a single electric motor connected to the axle shaft through an open differential.
The assessment of fuel economy of new vehicles is typically based on regulatory driving cycles, measured in an emissions lab. Although, the regulations built around these standardized cycles have strongly contributed to improved fuel efficiency, they are unable to cover the envelope of operating and environmental conditions the vehicle will be subject to when driving in the “real world”. This discrepancy becomes even more dramatic with the introduction of Connectivity and Automation, which allows for information on future route and traffic conditions to be available to the vehicle and powertrain control system. Furthermore, the huge variability of external conditions, such as vehicle load or driver behavior, can significantly affect the fuel economy on a given route. Such variability poses significant challenges when attempting to compare the performance and fuel economy of different powertrain technologies, vehicle dynamics and powertrain control methods.
Onboard sensing and external connectivity using Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies will allow a vehicle to "know" its future operating conditions with some degree of certainty, greatly narrowing prior information gaps. The increased development of such Connected and Automated Vehicle (CAV) systems, currently used mostly for safety and driver convenience, presents new opportunities to improve the energy efficiency of individual vehicles. The NEXTCAR program is one such initiative by the Advanced Research Projects Agency – Energy (ARPA-E) to developed advanced vehicle dynamics and powertrain control technologies that leverage such connected information streams. Southwest Research Institute (SwRI) in collaboration with Toyota and University of Michigan is currently working on improving energy consumption of a Toyota Prius Prime 2017 by 20%.
This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Coordinated Adaptive Cruise Control (CACC), Eco Approach and Departure (EcoAND) and in-situ vehicle parameter characterization.
The test cycle average drag coefficient is examined for the variation of allowable EPA coastdown ambient conditions. Coastdown tests are ideally performed with zero wind and at SAE standard conditions. However, often there is some variability in actual ambient weather conditions during testing, and the range of acceptable conditions is further examined in detail as it pertains to the effect on aerodynamic drag derived from the coastdown data. In order to “box” the conditions acceptable during a coastdown test, a sensitivity analysis was performed for wind averaged drag ((CDW ) ̅) as well as test cycle averaged drag coefficients (CDWC) for the fuel economy test cycles. Test cycle average drag for average wind speeds up to 16 km/h and temperatures ranging from 5C to 35C, along with variation of barometric pressure and relative humidity are calculated. The significant effect of ambient cross winds on coastdown determined drag coefficient is demonstrated.
The use of Wankel rotary engines as a range extender has been recognised as an appealing method to enhance the performance of Hybrid Electric Vehicles (HEV). They are effective alternatives to conventional reciprocating piston engines due to their considerable merits such as lightness, compactness, and higher power-to-weight ratio. However, further improvements on Wankel engines in terms of fuel economy and emissions are still needed. The objective of this work is to provide an engine modelling methodology that is particularly suitable for the theoretical studies on Wankel engine dynamics and new control development. In this paper, a control-oriented model is developed for a 225CS Wankel rotary engine produced by Advanced Innovative Engineering (UK) Ltd. Through a synthesis grey-box approach that combines State Space (SS) and artificial Neural Networks (NN), a model is derived by leveraging both first-principle knowledge and engine test data.
Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are non-causal and are typically intended for evaluating emission and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies.
We have proposed a new compressive combustion principle based on pulsed supermulti-jets colliding through focusing process, by injection from chamber wall to chamber center. This principle has potential of relatively-silent high compression around chamber center because of auto-ignition far from chamber wall and nearly-complete air insulation due to encasing of burned high temperature gas. The present principle leading to higher thermal efficiency and higher power will be applicable for automobiles, aircrafts, rockets, and also flying cars to be realized in the future. Then, water cooling system made smaller or even eliminated will result in lower price, while auto-ignition in an area larger than that created by traditional spark-ignition will lead to less NOx emission at very lean burning.
Based on the first sedan of the LYNK&CO brand from Geely, a high performance configuration with the additional aerodynamic package was developed. The aerodynamic package including the front wheel deflector, the front lip, the side skirt, the rear spoiler and the rear diffuser, were upgraded to generate enough aerodynamic downforce for better handing stability, without too much compromising of the aerodynamic drag of the vehicle to keep a low fuel consumption. Simulation approach with PowerFLOW, combined with the design space exploration method were used to optimize both of the aerodynamic lift and drag. Wind tunnel test was also used to firstly calibrate the simulation results and finally to validate the optimized design. The results turn out to be appropriate trade-off between the lift and the drag to meet the aerodynamics requirement, and a consistently good matching between the simulation and test.
With emission reduction taken as the priority by the whole society, in order to cut down on the fuel consumption for automotive manufacturers, aerodynamics plays a significant role in optimizing the exterior configuration for developing low drag vehicles. Of all the optimization approaches, the gradient-based adjoint method has currently gained much attention for its high efficiency in calculating the observables sensitivity with respect to shape parameter variation, which is the first step for subsequent shape optimization. In this work, the main goal is to evaluate the adjoint method on optimizing the vehicle shape for a lower drag design based on a production SUV. Firstly, the influence of different mesh schemes were discussed on sensitivity calculation results of aerodynamic drag. According to the sensitivity results, several key areas, like the side mirrors, the rear spoiler, the diffusor and the rim of the wheels, were respectively altered through mesh morphing process.
Today’s transportation is quickly transforming with the advent of shared-mobility, vehicle electrification, connected vehicle technology, and vehicle automation. These technologies will not only affect our safety and mobility, but also our energy consumption, air pollution, and climate change. As a result, it is of unprecedented importance to understand the overall system impacts, as a result of introducing these emerging technologies and concepts. However, existing modeling tools are not able to properly capture the implications of these technologies, not to mention accurately and reliably evaluating their effectiveness with a reasonable scope. For example, it is quite challenging to calibrate state-of-the-art microscopic traffic simulators to properly model the behavior of automated vehicles or to address potential cyber-security issues in a Connected Vehicle (CV) environment.