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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.

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.

A sampling system was developed to measure the evolution of the speciated hydrocarbon emissions from a single-cylinder SI engine in a simulated starting and warm-up procedure. A sequence of exhaust samples was drawn and stored for gas chromatograph analysis. The individual sampling aperture was set at 0.13 s which corresponds to ∼ 1 cycle at 900 rpm. The positions of the apertures (in time) were controlled by a computer and were spaced appropriately to capture the warm-up process. The time resolution was of the order of 1 to 2 cycles (at 900 rpm). Results for four different fuels are reported: n-pentane/iso-octane mixture at volume ratio of 20/80 to study the effect of a light fuel component in the mixture; n-decane/iso-octane mixture at 10/90 to study the effect of a heavy fuel component in the mixture; m-xylene and iso-octane at 25/75 to study the effect of an aromatics in the mixture; and a calibration gasoline.

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.

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.