What is a hybrid electric vehicle? Quite simply, a hybrid electric vehicle combines a minimum of one motor with an internal-combustion engine to maneuver the car, and its system recaptures energy via regenerative braking. Sometimes the electrical motor does all the work, sometimes it is the internal-combustion engine and sometimes they work together. The result is less gasoline burned and, therefore, better fuel economy and less pollution. Adding electrical power can even boost performance in certain instances. Electricity comes from a high-voltage battery pack (separate from the car's conventional 12-volt battery) that's replenished by capturing energy from deceleration that's typically lost to heat generated by the brakes in conventional cars (this happens through the regenerative braking system). Hybrids also use the internal-combustion engine to charge and maintain the battery. Car companies use different hybrid designs to accomplish different missions like maximum fuel savings, increased battery life, low greenhouse gas emission, low electrical and mechanical losses, etc. Not just regenerative breaking, the HEVs use various advanced technologies to achieve its purpose, like the electric motor providing power to help the engine in accelerating, passing, or hill climbing, this enables a smaller, moreefficient engine to be used. In some hybrids, the electric motor alone propels the vehicle at low speeds on situations where where gasoline engines are least efficient like climbing hills.

The latest methods for minimizing the power loss in real-time is based on adaptive adjustment of flux levels in order to determine the optimum operating point by minimizing electrical losses and using waste heat from air conditioners. It is done by developing power conditioning circuit using maximum power point tracking so that the output power of the proposed hybrid energy system can be maximized. According to recent studies, General motors is using shape memory alloys that require as little as 10oC temperature difference to convert low grade waste heat into mechanical energy.

Power is made to split smoothly between the vehicle propulsion and the generator using a power spit device further assisting the purpose of HEVs, in the process making it is a more complex electro-mechanical system which makes it difficult to construct an accurate mathematical model. Fuzzy control seems to be appropriate for the HEV control problem. Based on the state-of- charge (SOC) of the batteries and therefore the power information, the facility required by the vehicle is split between the engine/generator set and therefore the batteries instantaneously by the fuzzy logic controller. The SOC of the batteries are often maintained always at a high level and therefore the engine can steadily add its high efficiency area. A forward simulation model for the vehicle is established, and both off-line and real-time simulations are performed.

What is fuzzy control? When a situation is vague, the computer may not be able to produce a result that is True or False. As per Boolean logic, the worth 1 refers to True and 0 means False, but a symbolic logic algorithm considers all the uncertainties of a problem, where there may be possible values besides True or False like Certainly yes, Possibly yes, Can’t say, Possibly, Certainly no and gives a solution based on human inputs. Fuzzy control may seem like the perfect solution for dealing with this complex system but the fuzzy logic has disadvantages which might hold back the full capability of hybrid electric vehicle, hence compromising on its purpose. Fuzzy logic isn't always accurate, therefore the results are perceived by assumption and imprecise data. Setting exact, fuzzy rules and, membership functions is a difficult task.

Artificial intelligence(AI) is already under use in various different fields, although none of these have true intellect they are good mimics and some examples of AI being used today are in the transportation industry. Commercial planes are equipped with artificial intelligence that greatly aids the pilots during take-off and landing and sometimes out-perform the pilots during foggy landings. It is also used in the rail and shipping industry where it plans efficient routes. Even everyday mapping services such as google maps uses AI to provide navigation for its customers. Another big development in AI is in the use of self-driving cars. Already there are partially autonomous cars in the market and even a taxi company that uses fully autonomous vehicles. At the current pace of development AI will soon be in more appliances and they will provide more efficient energy saving methods.

Due to the complex structure of HEVs, the design of control strategies is a challenging task. The main objective of the control strategy is to satisfy the driver’s power demand with minimum fuel consumption and toxic emissions and with optimum vehicle performance. Moreover, fuel economy and emissions minimization are conflicting objectives; a sensible control strategy and AI might be able to satisfy the trade-off between them. Computerized technology currently found in these vehicles are not that efficient. Most, HEVs simply revert to conventional fuel once the battery is drained so to tackle this we can use artificial intelligence. Neural networks, also referred to as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a subset of machine learning and are at the guts of deep learning algorithms. This structure of Neural networks makes it suitable for any real time application.

ANN is a powerful computational method which learns from training data. This uses the principle of function approximation. The output of a neuron is a function of the weighted sum of the inputs and a bias, it also uses activation functions and is optimized using back propagation. The function of the whole neural network is just the computation of the outputs of all the neurons. A well-structured neural network can be trained using training data to make its predictions precisely. ANN is an efficient approach for pattern recognition and performance fitting. ANN and Fuzzy logic are often used for implementing a load levelling strategy and implemented a supervisory controller, which takes care of fuel economy and reduced emissions just in case of different drivers and driving pattern for analysis and control of power split during a parallel HEV. If AI can effectively control the power split and achieve the full purpose and efficiency of hybrid electric vehicle, this might be the closest we could get to a 100% efficiency and 0% pollution in automobiles and this will make governments of the world to rethink their decisions on banning hybrid electric vehicles.

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