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In this paper, we propose algorithms for cost minimization of physical wires that are used to connect electronic devices in the vehicle. The wiring cost is one of the most important drivers of electrical architecture selection. Our algorithms perform wire routing from a source device to a destination device through harnesses, by selecting the optimized wire size. In addition, we provide optimized splice allocation with limited constraints. Based on the algorithms, we develop a tool which is integrated into an off-the-shelf optimization and workflow system-level design tool. The algorithms and the tool provide an efficient, flexible, scalable, and maintainable approach for cost analysis and architecture selection.

To provide a feasible transitional solution from all-by-human driving style to fully autonomous driving style, this paper proposed concept and its control algorithm of a robust lane-keeping ‘co-pilot’ system. In this a semi-autonomous system, Learning based Model Predictive Control (LBMPC) theory is employed to improve system's performance in target state tracking accuracy and controller's robustness. Firstly, an approximate LTI model which describes driver-vehicle-road closed-loop system is set up and real system's deviations from the LTI system resulted by uncertainties in the model are regarded as bounded disturbance. The LTI model and bounded disturbances make up a nominal model. Secondly, a time-varying model which is composed of LTI model and an ‘oracle’ component is designed to observe the possible disturbances numerically and it is online updated using Extended Kalman Filter (EKF).

An investigation into two new control strategies for the vehicle Anti-lock Braking System (ABS) are made for a possible replacement of current non-optimal slip control methods. This paper applies two techniques in order to maximize the braking force without any wheel locking. The first considers the power dissipated by the brake actuator. This power method does not use slip to construct its reference signal for control. A heuristic approach is taken with this algorithm where one searches for the maximum power dissipated. This can open up easier implementation of regenerative braking concurrently with ABS on an electro-hydraulic braking system. Parameter scheduling is explored in this algorithm. The second algorithm employs the use of perturbation based Extremum Seeking Control (ESC) to provide a reference slip and a Youla controller in a negative feedback loop.

Optimizing/maximizing regen braking in a hybrid electric vehicle (HEV) is one of the key features for increasing fuel economy. However, it is known [1] that maximizing regen braking by braking the rear axle on a low friction surface results in compromising vehicle stability even in a vehicle which is equipped with an ESP (Enhanced Stability Program). In this paper, we develop a strategy to maximize regen braking without compromising vehicle stability. A yaw rate stability control system is designed for a hybrid electric vehicle with electric rear axle drive (ERAD) and a “hang on” center coupling device which can couple the front and rear axles for AWD capabilities. Nonlinear models of the ERAD drivetrain and vehicle are presented using bond graphs while a high fidelity model of the center coupling device is used for simulation.

We assessed the engine-out emissions of an ultra-low sulfur diesel (ULSD) and a neat hydrogenated vegetable oil (HVO) from a light-duty diesel truck equipped with common rail direct injection. The vehicle was tested at least twice on each fuel using the LA-92 drive cycle and at steady-state conditions at 30 mph and 50 mph at different loads. Results showed reductions in the engine-out total hydrocarbon (THC), carbon monoxide (CO), nitrogen oxide (NOx), and particulate emissions with HVO. The reductions in soot mass, solid particle number, and particulate matter (PM) mass emissions with HVO were due to the absence of aromatic and polyaromatic hydrocarbon compounds, as well as sulfur species, which are known precursors of soot formation. Volumetric fuel economy, calculated based on the carbon balance method, did not show statistically significant differences between the fuels.

Biofuels, such as ethanol and butanol, have been the subject of significant political and scientific attention, owing to concerns about climate change, global energy security, and the decline of world oil resources that is aggravated by the continuous increase in the demand for fossil fuels. This study evaluated the potential emissions impacts of different alcohol blends on a fleet of modern gasoline vehicles. Testing was conducted on a fleet of nine vehicles with different combinations of ten fuel blends over the Federal Test Procedure and Unified Cycle. The vehicles ranged in model year from 2007-2014 and included four vehicles with port fuel injection (PFI) fueling and five vehicles with direct injection (DI) fueling. The ten fuel blends included ethanol blends at concentrations of 10%, 15%, 20%, 51%, and 83% by volume and iso-butanol blends at concentrations of 16%, 24%, 32%, and 55% by volume, and an alcohol mixture giving 10% ethanol and 8% iso-butanol in the final blend.

Gasoline direct injection (GDI) engines have improved thermodynamic efficiency (and thus lower fuel consumption) and power output compared with port fuel injection (PFI) and their penetration is expected to rapidly grow in the near future in the U.S. market. In addition, the use of alternative fuels is expanding, with a potential increase in ethanol content beyond the current 10%. Increased emphasis has been placed on butanol due to its more favorable fuel properties, as well as new developments in production processes. This study explores the influence of mid-level ethanol and iso-butanol blends on criteria emissions, gaseous air toxics, and particulate emissions from two wall-guided gasoline direct injection passenger cars fitted with three-way catalysts. Emission measurements were conducted over the Federal Test Procedure (FTP) driving cycle on a chassis dynamometer.

The paper presents reportage of the debate on the topic expressed by its title that was held as a special session at the SAE 2003 Congress, supplemented by commentaries on its highlights. The debate brought to focus the fact that fuel cells are, indeed, superb powerplants for automobiles, while hydrogen is at the pinnacle of superiority as the most refined fuel. The problems that remained unresolved, are: (1) when fuel cells will be practically viable to replace internal combustion engines and (2) under what circumstances hydrogen, as the ultimate fuel, will be economically viable in view of its intrinsically high cost and hazards engendered by its extraordinary flammability and explosive tendency.

1 The topic of investigation of this work was the influence of different gas qualities on the engine parameters and particularly on the air excess factor λ. For this research the normalized gases with extreme compositions were used. At stationary operation there are no differences of the leaning capability of the different gases. The gas with the highest content of inert components causes the lowest full load power, the highest fuel consumption and the highest cyclic irregularity. With the same air flow and the same injection duration for different gases result different air excess factors λ according to the density and to the necessary stoichiometric air quantity of each gas. This fact influences the λ at transient operation conditions as: cold starting, gas quality jump, or load increase, if there is no λ-control. With an active λ-control, which is today fast enough, especially with an adaptive system there are no problems with λ- differences.

The measurement of SO2 levels in vehicle exhaust can provide important information in understanding the relative contribution of sulfur and sulfate from fuel vs. oil source to PM. For this study, a differential optical absorption spectrometer (DOAS) that can measure SO2 down to 20 ppbV in real-time was built and evaluated. The DOAS consisted of an extractive sampling train, a cylindrical sampling cell with a single-path design to minimize cell volume, a spectrometer, and a deuterium lamp light source with a UVC range of ∼200-230 nanometer (nm). Laboratory tests showed detection limits were approximately in the range of 12 to 15 ppbV and showed good linearity over SO2 concentration ranges of 20 to 953 ppbV. Interference tests showed some interference by NO and by NH3, at levels of 300 ppmV and 16.6 ppmV, respectively.

Verification and validation (V&V) are essential stages in the design cycle of industrial controllers to remove the gap between the designed and implemented controller. In this study, a model-based adaptive methodology is proposed to enable easily verifiable controller design based on the formulation of a sliding mode controller (SMC). The proposed adaptive SMC improves the controller robustness against major implementation imprecisions including sampling and quantization. The application of the proposed technique is demonstrated on the engine cold start emission control problem in a mid-size passenger car. The cold start controller is first designed in a single-input single-output (SISO) structure with three separate sliding surfaces, and then is redesigned based on a multiinput multi-output (MIMO) SMC design technique using nonlinear balanced realization.

This paper presents a driver assistance system designed to minimize the effect of driver reaction time on lane and speed maintenance operations. Nearly-instantaneous correcting actions are provided through a hierarchical arrangement of behaviors, by avoiding the time lag associated with deliberative or planning steps found in many control algorithms. Concepts originating in the field of robotics, including artificial potential fields and behavior-based systems, are interpreted for application to automotive control, where vehicle dynamics places considerable practical constraints on implementation. Ideas found in the study of emergent behavior in nature provide continuous, non-stepwise control signals, suitable for additive corrective inputs at highway velocities. This approach is effective for a substantial subset of road automobiles operating over a variety of speeds.

Although various legislation and regulations have been adopted to promote the use of alternative-fuel vehicles for curbing urban air pollution problems, there is a lack of systematic comparisons of emission control cost-effectiveness among various alternative-fuel vehicle types. In this paper, life-cycle emission reductions and life-cycle costs were estimated for passenger cars fueled with methanol, ethanol, liquified petroleum gas, compressed natural gas, and electricity. Vehicle emission estimates included both exhaust and evaporative emissions for air pollutants of hydrocarbon, carbon monoxide. nitrogen oxides, and air-toxic pollutants of benzene, formaldehyde, 1,3-butadiene, and acetaldehyde. Vehicle life-cycle cost estimates accounted for vehicle purchase prices, vehicle life, fuel costs, and vehicle maintenance costs.

The Oppenheim Correlation (OPC) is a new empirical algorithm, which allows a simple estimate of heat losses to the wall during the combustion in IC-engine. In present paper the results of different applications of OPC will be shown. Even if there are still several needs and ideas for further research it can be stated, that the OPC is a promising possibility of modeling the wall heat losses and due to its simplicity it has to be recommended to the engine community. The OPC can be used not only for didactics purposes, but also for quick simulation of wall heat losses and eventually for the on-line regulation of the cooling system.

This paper presents an energy-optimal deceleration planning system (EDPS) to maximize regenerative energy for electrified vehicles on deceleration events perceived by map and navigation information, machine vision and connected communication. The optimization range for EDPS is restricted within an upcoming deceleration event rather than the entire routes while in real time considering preceding vehicles. A practical force balance relationship based on an electrified powertrain is explicitly utilized for building a cost function of the associated optimal control problem. The optimal inputs are parameterized on each computation node from a set of available deceleration profiles resulting from a deceleration time model which are configured by real-world test drivings.

For automotive applications, it is necessary to maximize the fuel conversion efficiency of a PEM direct-methanol fuel cell (DMFC) over the broadest possible dynamic range of power. The research reported here critically examines the efficiency of the DMFC stack when operated over a broad power range. This research establishes a basis for a control strategy that simultaneously: optimizes DMFC fuel conversion efficiency versus power level, leads into a system level optimization of efficiency vs. power, and provides an operational strategy for controlling a direct-methanol fuel cell for maximum fuel efficiency from minimum to maximum power demand. First, there is an explanation of the experimental conditions used to obtain the DMFC experimental data that is reported and analyzed. Next the DMFC methanol crossover phenomenon is discussed and characterized. Then the conceptual framework for the optimization of fuel conversion efficiency is presented.

The question of whether or not direct-hydrogen fuel cell systems in automotive applications should be used in load following or load leveled (battery hybrid) configurations is addressed. Both qualitative and quantitative analyses are performed to determine the potential strengths and weaknesses of each option. It is determined that the amount of energy that can be recovered through regenerative braking has a strong impact on the relative fuel economy of load following versus load leveled operation. Further, it is demonstrated that driving cycles with lower power requirements will show an improvement in vehicle fuel economy from hybridization while those with higher power requirements will not. Finally it is acknowledged that the practical considerations of cost and volume must also weigh heavily into the decision between the two configurations.

Simultaneous control of speed and air-fuel ratio in a six-cylinder automobile engine is studied. A three-state engine model including rotational, air intake and fuel intake dynamics is used for control design. Control design focuses on application of nonlinear control techniques, specifically sliding mode control. Controllers are designed for tracking speed profiles and regulating air-fuel mixture. Multiple-surface sliding control is shown to result in good speed tracking in simulation and experiment. The production fuel controller and an observer-based sliding controller are shown to result in the best fuel control during speed transients. A standard sliding fuel controller is shown to result in high amplitude deviations due to oxygen sensor time delay. The best combination of controllers is shown to be the multiple-surface sliding speed controller and the observer-based fuel controller.

The relationship between ethanol and iso-butanol fuel concentrations and vehicle particulate matter emissions was investigated. This study utilized a gasoline direct injection (GDI) flexible fuel vehicle (FFV) with wall-guided fueling system tested with four fuels, including E10, E51, E83, and an iso-butanol blend at a proportion of 55% by volume. Emission measurements were conducted over the Federal Test Procedure (FTP) driving cycle on a chassis dynamometer with an emphasis on the physical and chemical characterization of particulate matter (PM) emissions. The results indicated that the addition of higher ethanol blends and the iso-butanol blend resulted in large reductions in PM mass, soot, and total and solid particle number emissions. PM emissions for the baseline E10 fuel were characterized by a higher fraction of elemental carbon (EC), whereas the PM emissions for the higher ethanol blends were more organic carbon (OC) in nature.

This paper follows a cycle-simulation method for creating an engine performance map for an ethanol fueled boosted HCCI engine using a 1-dimensional engine model. Based on experimentally determined limits, the study defined operating conditions for the engine and performed a limited parameter sweep to determine the best efficiency case for each condition. The map is created using a 6-Zone HCCI combustion model coupled with a detailed chemical kinetic reaction mechanism for ethanol, and validated against engine data collected from a 1.9L 4-Cylinder VW TDI engine modified to operate in HCCI mode. The engine was mapped between engine speeds of 900 and 3000 rpm, 1 and 3 bar intake pressure, and 0.2 and 0.4 equivalence ratio, resulting in loads between idle and 14.0 bar BMEP. Analysis of a number of trends for this specific engine map are presented, such as efficiency trends, effects of combustion phasing, intake temperature, engine load, engine speed, and operating strategy.