An effective energy management strategy in hybrid electric vehicles using Taguchi based approach for improved performance

Abstract

The key challenge in the innovation of hybrid electric vehicles is the energy management control strategies to split the energy between the sources. The objective of adding an auxiliary source of power to vehicles is to minimize battery stress as well as energy consumption rate (ECR) of the main source and to increase the range of the vehicle. Based on Taguchi and grey relational analysis, the optimal control factors were determined for each of the desired performance factors. In this experimental design, control strategy, vehicle model, battery SOC, and UC SOC are considered as control factors, and ECR, range of the vehicle, and battery stress remain as vehicle performance factors. The confirmatory results show the minimal error between the initial set and the optimum factor to be 7.68 for ECR, 8.54 for range, and 5.49 for battery stress, respectively. The results also reveal the importance of fuzzy-based strategy on hybridization of energy storage systems in electric vehicles and also identified the most and the least influencing factors that affect the vehicle performance.