Search Results

While graphics processing units (GPUs) and application-specific integrated circuits (ASICs) have been used to improve performance in AI-based applications, field-programmable gate arrays (FPGAs) have gained popularity due to their low power consumption and high-speed acceleration, making them ideal for artificial intelligence (AI) implementation. One of the critical components of EVs and HEVs is the BMS, which performs operations to optimize the use of energy stored in lithium-ion batteries (LiBs).

Abstract Electric vehicles (EVs) with enormous batteries are capable of storing a high quantity of energy. This stored energy can be used as a standby power supply or as backup energy storage for domestic loads whenever a blackout or load shedding happens. Further, solar photovoltaic (PV) energy can also be utilized to charge the battery of EV and also improve the backup energy source for domestic loads. The main purposes of this article are to reduce the energy cost of a household and also to minimize the dependency of domestic loads on the grid, to enhance the reliability of power supply to the residential loads during load shedding and blackouts, and to maximize the utilization of power produced by the solar photovoltaic array (SPVA) mounted on the rooftop. Moreover, Alternating Current (AC) loads are connected to the AC bus, and Direct Current (DC) loads are connected separately to the DC bus to avoid power losses in conversion (DC to AC and AC to DC).

With the goal to build a cellular battery model, it was developed a Neural Network Artificial (ANN), with a learning capacity and adaptation to the charge cycles, discharge and rest to the Lithium-Ion battery. ...With that said, this paper has the objective of obtaining a model and a estimation from the SoC based in Neural Network Artificial (ANN).

This work presents a discussion on the causes and effects of thermal avalanches in artificial satellite battery charging and discharging systems. To do so it: 1) revises the literature on the known causes and effects; 2) develops a block diagram model for a battery charging and discharging system in artificial satellites, based on macroscopic principles which can be generalized to a wide variety of topologies and technologies of power supply and batteries; 3) discusses new causes and effects. ...To do so it: 1) revises the literature on the known causes and effects; 2) develops a block diagram model for a battery charging and discharging system in artificial satellites, based on macroscopic principles which can be generalized to a wide variety of topologies and technologies of power supply and batteries; 3) discusses new causes and effects.

The capacity estimated using the semi-empirical model is further taken as the inputs for estimating capacity using the Artificial Neural Network (ANN) and Machine Learning (ML) techniques i.e., Linear Regression (LR), Gaussian Process Regression (GPR), Support Vector Machine methods (SVM). ...., Linear Regression (LR), Gaussian Process Regression (GPR), Support Vector Machine methods (SVM). Artificial Neural Network model has been trained in the neural fitting application in MATLAB and the trained neural network model is exported to Simulink and analysed.

This research aims at developing the suboptimal energy management strategy by using artificial neural network (ANN) for a triple-electrical-energy electric vehicle (EV). The controller hardware designs will be implemented in the future.

The obtained results provide useful information for both producers of Battery Electric Vehicle (BEV) Energy Storage Systems (ESS) in the design stage, and for artificial intelligence driver support systems, mainly focused on extending overall vehicle life.

Editorial Of moose and artificial intelligence Supplier Eye Moons aligning Magna's drop-in, off-road electric powertrain Tenneco opens engineering, simulation center in Poland Automaker coalition plans high-power charging network Fully charged in six minutes?

Conversely, the imminent and rapid progression of artificial intelligence (AI) is poised to have a substantial impact on the forthcoming landscape of work and the methodologies organizations employ for the management of their knowledge management (KM) procedures.

A new artificial intelligence (model order reduction) / finite element coupled approach will be presented for the risk assessment of battery fire during a car crash event.

October 29-31, 2019 │ Novi, MI

October 29-31, 2019 │ Novi, MI

October 29-31, 2019 │ Novi, MI

Concurrent administration of standard intelligence tests was performed, along with paper-and-pencil versions of the computer tests. Nine of the 11 tests stabilized by the third administration (inertial correlations high and consistent). ...Regression of the full battery against intelligence yielded high multiple correlations (r=.70).

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

Lighter-Than-Air type stratospheric long duration platforms, now under development, are re-deployable vehicles which play identical roles as artificial satellites except that LTA platforms can be recovered, refit and launched again in case of malfunction and after their lifetime service, all of them can be recovered, unlike satellites resulting in space debris and further atmospheric contamination.

October 29-31, 2019 │ Novi, MI