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Cited by 51 publications
(25 citation statements)
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References 28 publications
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“…The authors showed a 2.4% fuel economy improvement over the conventional A-ECMS algorithm. Kazemi et al [32] further developed adaptations to the A-ECMS for use in a parallel HEV and assessed the prediction window size and the effects it had on the EF and resulting improvements over the A-ECMS. The study concluded that future investigation would be required but found that a prediction window larger than 15s started to degrade performance.…”
Section: Real-time Optimization Hybrid Algorithmsmentioning
confidence: 99%
See 2 more Smart Citations
“…The authors showed a 2.4% fuel economy improvement over the conventional A-ECMS algorithm. Kazemi et al [32] further developed adaptations to the A-ECMS for use in a parallel HEV and assessed the prediction window size and the effects it had on the EF and resulting improvements over the A-ECMS. The study concluded that future investigation would be required but found that a prediction window larger than 15s started to degrade performance.…”
Section: Real-time Optimization Hybrid Algorithmsmentioning
confidence: 99%
“…[37] developed a model-predictive control strategy for a diesel hybrid vehicle that considered engine transient characteristics and showed potential for improving fuel economy of the vehicle. Kazemi et al [32] applied the A-ECMS algorithm with additional adaptation based on a prediction horizon to a parallel HEV, with a spark ignition engine. The authors also worked to reduce engine transients using this algorithm, defined as engine on/off events.…”
Section: Engine Transient Impacts On Emissions and Fuel Economymentioning
confidence: 99%
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“…The primary means of accomplishing these goals is to develop an algorithm that optimizes the power distribution between the ICE powertrain and electric powertrain. There are many control scheme methodologies that have been applied to achieve these goals such as predictive algorithms to learn driving behaviors in [9], vehicle-to-everything communication (V2X) to improve the vehicle's awareness of its surroundings [10], a golden section search algorithm coupled with a various cost functions to optimize the torque distribution of the powertrains, transmission control development for a hybrid-electric vehicle architecture, or something as simple as a binary, or ON-OFF, approach for when to use each powertrain. The research within this thesis will focus on the development and optimization of a gear shifting schedule for the transmission in a P3 parallel hybrid-electric vehicle.…”
Section: Hybrid-electric Powertrain Control Developmentmentioning
confidence: 99%
“…A revolutionary age of modern driving has been initiated by the advent of safety and comfort driving applications that aim at assisting drivers in vehicle control. Forward collision warning [5,6,7,8], lane keep assistance [9,10,11], automatic braking [12], adaptive cruise control [13,14], efficiency [15,16], and pedestrian safety [17,18,19] systems are amongst the most important automated driving applications. The first generation of safety applications was designed by virtue of local sensors such as radars and cameras.…”
Section: Introduction 11 Problem Definitionmentioning
confidence: 99%