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In order to study the noise effect of the crank angle sensor on electronic fuel injection (EFI) control system, a Kalman filter with stroke identification is employed to estimate the crankshaft rotational dynamics. Estimated crank angle and speed are then used for EFI system. A 125 c.c. scooter engine verified by the experimental data is used to design the Kalman filter. A simulation model, which consists of nonlinear engine dynamics, powertrain dynamics, tire dynamics, and pitch-plane motorcycle dynamics, is established in Matlab/Simulink to evaluate the performance of the Kalman filter at various noise conditions.

Electronic Control has been widely used in automotive systems, such as Vehicle Dynamics Control, Anti-Lock Braking Systems, Active Suspension and Steering System control, etc. The rapid prototyping development of an embedded controller for an electronic power assisted steering system (EPAS) will be presented in this paper. A steering model is established in MATLAB/SIMULINK to verify the proposed EPAS in this paper. This model includes the effects of kingpin inclination, caster, camber and lateral offset to calculate the total steering torque. The EPAS control strategy has considered the driver commands and vehicle speed to provide multiple stages of steering torque assistance. TMS320F240 DSP is used as the embedded controller of EPAS. EPAS Control algorithms have been designed using MATLAB/SIMULINK/Real-Time Workshop and Input/Output of Blocksets of TMS320F240 DSP have been developed in SIMULINK.

For a conventional scooter engine, not only the crankshaft position estimation is insufficient based on the one-tooth crankshaft wheel, but also the speed measurement might be contaminated by sensor noise easily. The authors propose a technique using Kalman filter to estimate crankshaft position and engine speed for digital ignition control of a scooter engine. A 125cc engine model, which is verified by the experimental data of the target engine, will be used to design the Kalman filter. A simulation model, which consists of nonlinear engine dynamics, powertrain dynamics, tire dynamics, and pitch plane dynamics, is used to evaluate the performance of proposed estimation algorithm with different tooth numbers of crankshaft wheel and various noise conditions.

This paper presents the application of rapid prototyping electronic control unit (ECU) to fuel injection and ignition control of electronic fuel injection motorcycle engine by using Model-Based environment. As a scene on state of the art, it is famous accepted that the MATLAB Model-Based environment is an efficient development platform for engine management systems (EMS). These come from several benefits: (1) System level design environment, (2) Real-time simulation, and (3) Model to chip technology during rapid prototyping ECU development process. Therefore, this research uses these advantages to study the rapid prototyping controller (RPC) of a SI engine for decreasing time and cost requirements of development process. The target vehicle is a scooter with a four-stroke 125 cc. single cylinder engine.