Related papers: Energy-Efficient Adaptive System Reconfiguration f…
Driven by growing concerns over air quality and energy security, electric vehicles (EVs) has experienced rapid development and are reshaping global transportation systems and lifestyle patterns. Compared to traditional gasoline-powered…
Seasonal climate variations affect electricity demand, which in turn affects month-to-month electricity planning and operations. Electricity system planning at the monthly timescale can be improved by adapting climate forecasts to estimate…
Micro DC brushed motors are widely deployed in battery-powered biomedical systems, where limited energy budgets and variable physiological loading impose stringent efficiency and safety constraints. However, conventional actuation…
Domain-specific systems-on-chip (DSSoCs) aim at bridging the gap between application-specific integrated circuits (ASICs) and general-purpose processors. Traditional operating system (OS) schedulers can undermine the potential of DSSoCs…
The ability to adapt to changing environments is crucial for the autonomous navigation systems of Unmanned Aerial Vehicles (UAVs). However, existing navigation systems adopt fixed execution configurations without considering environmental…
In the realm of urban transportation, metro systems serve as crucial and sustainable means of public transit. However, their substantial energy consumption poses a challenge to the goal of sustainability. Disturbances such as delays and…
Real time system technology traditionally developed for safety critical systems, has now been extended to support multimedia systems and virtual reality. A large number of real-time application, related to multimedia and adaptive control…
Embedded systems are becoming more in demand to work in dynamic and uncertain environments, and being confined to the strong requirements of real-time. Conventional static scheduling models usually cannot cope with runtime modification in…
This paper proposes a robust optimal eco-driving control strategy considering multiple signalized intersections with uncertain traffic signal timing. A spatial vehicle velocity profile optimization formulation is developed to minimize the…
This paper presents an adaptive leading cruise control strategy for the connected and automated vehicle (CAV) and first considers its impact on the following human-driven vehicle (HDV) with diverse driving characteristics in the unified…
With the intensified use of intelligent things, the demands on the technological systems are increasing permanently. A possible approach to meet the continuously changing challenges is to shift the system integration from design to run-time…
This paper devotes to the development of an optimal acceleration/speed profile for autonomous vehicles approaching a traffic light. The design objective is to achieve both short travel time and low energy consumption as well as avoid idling…
Learning-based model predictive control has been widely applied in autonomous racing to improve the closed-loop behaviour of vehicles in a data-driven manner. When environmental conditions change, e.g., due to rain, often only the…
In autonomous electric vehicles (AEVs), battery energy must be judiciously allocated to satisfy primary propulsion demands and secondary auxiliary demands, particularly the Heating, Ventilation, and Air Conditioning (HVAC) system. This…
This paper establishes a novel analytical approach to quantify robustness of scheduling and battery management for battery supported cyber-physical systems. A dynamic schedulability test is introduced to determine whether tasks are…
Improving endurance is crucial for extending the spatial and temporal operation range of autonomous underwater vehicles (AUVs). Considering the hardware constraints and the performance requirements, an intelligent energy management system…
To improve the driving mobility and energy efficiency of connected autonomous electrified vehicles, this paper presents an integrated longitudinal speed decision-making and energy efficiency control strategy. The proposed approach is a…
This work presents a stochastic dynamic programming (SDP) algorithm that aims at minimizing an economic criteria based on the total energy consumption of a range extender electric vehicle (REEV). This algorithm integrates information from…
In this paper, we present the periodic modifier-adaptation formulation of the dynamic real time optimization. The proposed formulation uses gradient information to update the problem with affine modifiers so that, upon convergence, its…
Electric vehicles (EVs) have enjoyed increasing adoption because of the global concerns about the petroleum dependence and greenhouse gas emissions. However, their limited driving range fosters the occurrence of charging requests deriving…