Intelligent Power Allocation Strategy for Electric Vehicles

Abstract

Transportation plays a significant role in the global economy, and its energy re- quirement has increased tremendously to reach 29 %, with massive growth in the past decade. Meanwhile, the transportation industry has consumed almost 2/3rd of oil demand and nearly 1/4th of global carbon dioxide emissions from fossil fuel combustion. Moreover, a hike in fossil fuel costs and their reduced availability are other major issues that motivated the development of a green and clean mode of transportation. In that context, vehicles with an alternative energy source are essential. This highly motivated the development of battery electric vehicles and hybrid electric vehicles. Researchers have focused on investigating innovations with EVs. Although EVs are developed with improved performance and comfort, certain is- sues hinder their wider adoption. The Lithium-ion battery is one of the primary energy sources for electrified transportation. The battery performance of BEVs is affected by variations in different driving profiles and conditions. Vital factors that decide the performance of the EVs are 1) Battery life, 2) Range or mileage 3) Battery capacity fade costs. Hence investigation of these parameters is necessary for analyzing BEVs performance. Considering the recent advanced BEV technologies, the performance parame- ters are not up to the mark. Battery life - Battery degradation affects the max- imum power handling capability of the BEV battery, thus leading to poor per- formance of the vehicle. It reduces the life cycle of the battery and may initiate battery replacement. Range anxiety - The EV’s range or mileage decides the user’s anxiety. A reduced range creates range anxiety while driving since the charging stations are not ubiquitous. Capacity fade cost - This is an after-effect of battery life depletion. However, these are not similar for all users. It differs based on different driving conditions such as 1) Vehicle (starting, velocity, acceleration, and braking), 2) Driver (driving behaviors, route selection, charging, and usage patterns), 3) Environment (irradiance, ambient temperature, wind speed, road, and traffic conditions). Whenever the battery’s capacity reaches less than 75%, it is called the battery’s end of life. The battery fade costs must be reduced to increase the popularity of BEVs. The solution to such impacts on the BEVs high- lights the usage of hybrid sources in EVs. A supercapacitor coupled with a battery handles the transient load current of the EV traction. The SC response time and power density are higher than batteries; thus, it can ensure battery safety. Moreover, the regenerative braking energy can be recuperated in the SC, which improves energy efficiency. The en- ergy utilization of the transportation industry is increasing tremendously. 2/3rd iiiof total energy consumption will be occupied by renewable energy (wind, solar, bioenergy, geothermal, and hydro energy) by the end of 2050. Electrified trans- portation combined with renewable energy sources reduces emissions by 60 %. Utilizing renewable sources in the vehicle ensures a green, clean, and sustainable transportation sector. Developing countries with higher solar insolation can em- ploy solar panels to charge the EV sources during the daytime. They can achieve their daily commute with less number of charging from the grid. Therefore the contribution of Hybrid Source Electric Vehicles (HSEV) will be a significant step toward a sustainable future. The SC and PV are the auxiliary sources coupled with the Lithium-ion bat- tery in a proposed hybrid source system in EVs. An Intelligent Hybrid Source Energy Management Strategy (IHSEMS) employing a fuzzy logic-based controller is successfully introduced to overcome the issues and drawbacks of the existing electric vehicle systems ensuring an optimal source operations. The proposed al- gorithm ensures absolute energy sharing among each source and diminishes the impact of varying driving and environmental conditions. The proposed energy management strategy for HSEV improves the battery charge levels, increases the vehicle range, eliminates high C-rate instants, avoids frequent charge and dis- charging (fluctuations) in battery current profile, and improves the battery life. Moreover a modified energy management algorithm (EMA) is proposed for a high energy-dense SC and high conversion efficient PV panels based on a new hybrid energy vehicle. Investigations on different locations with varying driving and en- vironmental conditions are conducted to highlight the significance of the proposed hybrid source model. A detailed techno-economic assessment shows the signifi- cance of the proposed hybrid models and respective proposed energy management algorithms compared to BEVs and existing EMSs. Moreover, in countries with underdeveloped grid infrastructure, Solar PV in electric vehicle applications can be highly beneficial.