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With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

Diesel particulate filters (DPF) are a common component in emission-control systems of modern clean diesel vehicles. Several DPF materials have been used in various applications. Silicone Carbide (SiC) is common for passenger vehicles because of its thermal robustness derived from its high specific gravity and heat conductivity. However, a segmented structure is required to relieve thermal stress due to SiC's higher coefficient of thermal expansion (CTE). Cordierite (Cd) is a popular material for heavy-duty vehicles. Cordierite which has less mass per given volume, exhibits superior light-off performance, and is also adequate for use in larger monolith structures, due to its lower CTE. SiC and cordierite are recognized as the most prevalent DPF materials since the 2000's. The DPF traps not only combustible particles (soot) but also incombustible ash. Ash accumulates in the DPF and remains in the filter until being physically removed.

Semi-active suspension systems have traditionally used accelerometers mounted on the wheel and body to sense vehicle motion. However, the cost and weight of these sensors and their associated bracketry and wiring must be considered when deciding to adopt a semi-active suspension system on a particular vehicle. In previous report [1], Authors have described a Bi-Linear Optimal control algorithm [2] by which sprung mass motion is estimated using height sensor signals and a Kalman filter. Such an algorithm would eliminate the need for additional accelerometers and their associated hardware, resulting in a cheaper and lighter system. In this report, the Authors propose a method of improved ride comfort and reducing tuning time of this algorithm by improving the sprung mass motion estimation method.

Electric vehicles have a strong potential to reduce a continued dependence on fossil fuels and help the environment by reducing pollution. Despite the desirable advantage, the introduction of electrified vehicles into the market place continues to be a challenge due to cost, safety, and life of the batteries. General Motors continues to bring vehicles to market with varying level of hybrid functionality. Since the introduction of Li-ion batteries by Sony Corporation in 1991 for the consumer market, significant progress has been made over the past 25 years. Due to market pull for consumer electronic products, power and energy densities have significantly increased, while costs have dropped. As a result, Li-ion batteries have become the technology of choice for automotive applications considering space and mass is very critical for the vehicles.

We have developed a cooperative simulation environment for multiple electronic control units (ECUs) including a parallel executions mechanism to improve the test efficiency of a system, which was designed with multiple ECUs for autonomous driving. And we have applied it to a power window system for multiple ECUs with a controller area network (CAN). The power window model consists of an electronic-mechanical model and a CPU model. Each simulator with a different executions speed operates in parallel using a synchronization mechanism that exchanges data outputted from each simulator at a constant cycle. A virtual ECU simulated microcontroller hardware operations and executed its control program step-by-step in binary code to test software for the product version. As co-simulation technology, a mechanism that synchronously executes heterogeneous simulators and a model of an in-vehicle communication CAN connecting each ECU were developed.

Particulates were collected from the exhaust of a single cylinder diesel engine at different speeds and fuel-air equivalence ratios. The filters were rated to capture 99.99% of all particulates >0.3 microns in diameter. Samples were taken at 1500 RPM and equivalence ratios varying from about 0.2 to 0.7, and at an equivalence ratio of about 0.3 and engine speeds varying from 1000 to 2500 RPM. A base point with an equivalence ratio of 0.3 with an engine speed of 1500 RPM was repeated several times to establish the expected test variation of the particulate data. The particulate properties investigated were the total mass of particulate produced per mass of fuel burned, the mass fraction of extractable organic material in the sample, and the mutagenic potency of the extract as measured by a bacterial bioassay. Variation in fuel-air ratio (engine load) affected the particulate and extractable organic production much more than variations in engine speed.