A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City

Abstract

Electric Vehicles (EVs) have emerged rapidly across the globe as a powerful eco-friendly initiative that if integrated well with an urban environment could be iconic for the city’ host’s commitment to sustainable mobility and be a key ingredient of the smart city concept. This paper examines ways that will help us to develop a better understanding of how EVs can achieve energy use optimization and be connected with a smart city. As a whole, the present study is based on an original idea that would be useful in informing policy-makers, automotive manufacturers and transport operators of how to improve and embrace better EV technologies in the context of smart cities. The proposed approach is based on vehicles and buildings communication for sharing some special information related to the vehicle status and to the road condition. EVs can share their own information related to the energy experience on a specific path. This information can be gathered in a gigantic database and used for managing the power inside these vehicles. In this field, this paper exposes a new approach to power management inside an electric vehicle based on bi-communication between vehicles and buildings. The principle of this method is established on two sections; the first one is related to vehicles’ classification and the second one is attached to the buildings’ recommendation, according to the car position. The classification problem is resolved using the support vector classification method. The recommendation phase is resolved using the artificial intelligence principle and the neural network was employed, for giving the best decision. The optimal decision will be calculated inside the building, according to its position and using the old vehicle’s data, and transferred to the coming vehicle, for optimizing its energy consumption method in the corresponding building zone. Different possibilities and situations were discussed in this approach. The proposed power management methodology was tested and validated using Simulink/Matlab tool. Results related to the battery state of charge and to the consumed energy were compared at the end of this work, for showing the efficiency of this approach.

Variable reluctance synchronous machines in saturated mode

“…The saturation is calculated considering the induction in stator tooth can't achieve the saturation value of the iron B-H curve [17], [18]. The saturation values of inductances are measured using the linear model and the (19) to (22).…”

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“…The converter's estimated model is built on the manipulation of three voltage levels by a triangular signal. To replicate the evolution of the three phases supply voltages, the outputs of the three comparators attack two hysteresis depending from the value of the DC bus voltage Udc and 0 [20], [21] and [22].…”

Evaluation of Accommodation Capability for Electric Vehicles of a Distribution System Considering Coordinated Charging Strategies

“…The ever-increasing penetration of EV charging demand has been observed in many actual power distribution systems. As a new type of load (with a high degree of uncertainty), the integration of numerous EVs could bring great challenges to the secure and economic operations of the distribution system [4][5][6]. This may result in increasing energy losses, voltage deviations, and even overloads in feeders and/or substations.…”

“Smart Is Not Smart Enough!” Anticipating Critical Raw Material Use in Smart City Concepts: The Example of Smart Grids

“…CRMs such as silicon and graphite are needed for this type of battery construction [46]. Specifically, the dynamic growth of electric vehicles sales expected globally through 2030 [47] will provide new means of energy accumulation, which will jointly resolve smart cities' mobility and energy issues and result in increasing demand for cobalt [47,48]. This will increase the market domination of this type of battery, which already has an 85% share of the rechargeable battery market [49].…”