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Jia, Xianzhe
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High Efficiency Intake System Leveraging Exhaust Thermal Boost

Finitronx-Xianzhe Jia
University of Pennsylvania-Qianyu Ouyang
  • Technical Paper
  • 2020-01-0277
To be published on 2020-04-14 by SAE International in United States
This IC engine amelioration tackles the hurdling barrier of ICE’s intrinsic efficacy limit through innovative mechanical design of a consolidated system encompassing intake bypass and coordinating injection mechanism. To be specific, a CFD-optimized passage is constructed alongside the intake and injection design which utilizes multi-stage variable mixing precisely, taking full advantage of exhaust temperature elevation. Regenerative heat gained through exhaust system gives rise to flexible amount of thermal dynamics adjustment to the intake. Furthermore, variable geometry intake port is developed based on maximizing air-fuel interaction rate under different circumstances, where high temperature turbulence optimization is implemented in ANSYS Fluent. Pin-slider mechanic design at intake interface enables modular variable intake routing supporting engine efficiency promotion. Regarding ECU development, integrated valve, intake airflow, as well as injection control are designed to cooperate with each other under the supervisory control module. First, optimal controlled valve system is devised at the junction of bypass, which achieves improved response accuracy and combustion sufficiency with flow and temperature regulation. Secondly, a closed-loop injection control strategy fulfills variable in-cylinder combustion tuning with…
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An IMPC Based Parking Assistance System

FinitronX-Qianyu Ouyang, Xianzhe Jia
Published 2019-10-22 by SAE International in United States
This paper summarizes progress and outcome from our research projects on IMPC-based parking management system, including parking motion planning and control strategy, as well as a searching strategy for parking spot. IMPC here refers to interactive model predictive control regime, which is characterized in that multiple agents implementing separate MPC strategy are incorporating information about their state, objective, and constraints. To predict future parking parameters, we proposed a practical framework which integrates anticipatory techniques with a model predictive approach that robustly models the stochastic parking environment. The framework is able to take into account the interactions between vehicle subsystems, and can optimize trajectory under complex traffic patterns in real-world scenarios. Adaptive model predictive control is utilized to optimally minimize a cost function regarding performance, energy efficiency and drivability with regard to surrounding vehicle states. Dynamic programming was used to solve the control objective under multiple constraints, which yielded superior performance in comparison with convex programming. An original navigation system was developed for leading user to the parking spot in case of forgetting exact location, which…
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