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A novel torque-coupling architecture for hybrid electric vehicles is proposed. The torque-coupling device is based on automated manual transmission (AMT), which is highly efficient and provides six gears for the engine and three gears for each motor to enable the engine and the motors to work at high-efficiency levels in most cases. The proposed power-shift AMT (P-AMT) does not have a hydraulic torque converter and wet clutches, which dampen the driveline shock. Thus, the drivability control of the P-AMT becomes a challenging issue. Accurate engine, motor model and transmission model have been built and the dynamic control of the gear shift process of PAMT in hybrid mode is simulated. The electric motors compensate for the traction loss during the gear shift of the engine.

Artificial intelligence (AI)-based solutions are slowly making their way into our daily lives, integrating with our processes to enhance our lifestyles. This is major a technological component regarding the development of autonomous vehicles (AVs). However, as of today, no existing, consumer ready AV design has reached SAE Level 5 automation or fully integrates with the driver. Unsettled Issues in Vehicle Autonomy, AI and Human-Machine Interaction discusses vital issues related to AV interface design, diving into speech interaction, emotion detection and regulation, and driver trust. For each of these aspects, the report presents the current state of research and development, challenges, and solutions worth exploring. Click here to access the full SAE EDGETM Research Report portfolio.