Hybrid vehicleA hybrid vehicle is one that uses two or more distinct types of power, such as submarines that use diesel when surfaced and batteries when submerged. Other means to store energy include pressurized fluid in hydraulic hybrids. Hybrid powertrains are designed to switch from one power source to another to maximize both fuel efficiency and energy efficiency. In hybrid electric vehicles, for instance, the electric motor is more efficient at producing torque, or turning power, while the combustion engine is better for maintaining high speed.
Hybrid vehicle drivetrainHybrid vehicle drivetrains transmit power to the driving wheels for hybrid vehicles. A hybrid vehicle has multiple forms of motive power. Hybrids come in many configurations. For example, a hybrid may receive its energy by burning gasoline, but switch between an electric motor and a combustion engine. Electrical vehicles have a long history combining internal combustion and electrical transmission - as in a diesel–electric power-train - although they have mostly been used for rail locomotives.
Plug-in hybridA plug-in hybrid electric vehicle (PHEV) is a hybrid electric vehicle whose battery pack can be recharged by plugging a charging cable into an external electric power source, in addition to internally by its on-board internal combustion engine-powered generator. Most PHEVs are passenger cars, but there are also PHEV versions of sports cars, commercial vehicles and vans, utility trucks, buses, trains, motorcycles, mopeds, and even military vehicles.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
