Modelling and Assessment of Battery Electric Vehicle Powertrain and the Impact on Dynamic Characteristics in relation to Addis Ababa, Ethiopian Driving Profile

Abstract

In recent years, battery electric vehicles (BEVs) have gained attention due to their zero emissions and improved efficiency. However, their global market spread is hindered by the range anxiety of customers associated with a limited driving range and the requirement of long time to charge the battery. To alleviate the challenges, grid power forecasting, energy consumption estimation, range prediction and lifecycle analysis need to be addressed considering the use phase conditions. The BEV manufacturers are focusing on the market of developed countries and their operating cycle evaluation is also based on those countries. However, to increase market share, their development should explore new operating conditions and duty cycles, particularly for developing countries. This dissertation develops a Systems Engineering methodology for the integration of an electric powertrain within vehicle sizing and synthesis, specifically tailored to the driving profile of Addis Ababa, Ethiopia. It assesses energy consumption, powertrain efficiency, and dynamic performance characteristics in a virtual environment using valid models and a simulation setup. A new BEV driving cycle was developed for Addis Ababa, Ethiopia, using GPS-collected data and compared with the k-means clustering method and legislative drive cycles. This cycle was then integrated with powertrain sizing. Top-level energy-based modelling and subsystem parametric models were employed to validate the method and simulate country-specific energy consumption, powertrain efficiency, and driving range. According to the simulated results, acceleration requirements demand the maximum force and power, with low and high speeds needed for desired performance. The proposed BEV drive cycle shows a 14.57% and 8.9% reduction in energy consumption compared to the Urban Dynamometer Driving Schedule (UDDS) and Worldwide Harmonized Light Vehicles Test Cycle (WLTC)-2. The Addis Ababa and its suburbs (AASU) cycle demonstrated an average cycle efficiency of 88.7%, reaching 96% efficiency of the implemented electric motor. Additionally, the AASU cycle provided 5-20 km more range than the WLTC cycle, reducing the battery size by 3.4 kWh for urban car driving. Subsequently, a Finite Element Method (FEM) model of the body structure integrated with the powertrain package was analyzed for both aluminum and structural steel. The aluminum body structure exhibited a weight reduction of 11.75%, resulting in energy savings and extending the range by 18.21 km. The study, conducted in a Computer-Aided Design (CAD) model, also revealed that powertrain components packaging and side wind velocity impact aerodynamic drag and stability. The increase in drag force was attributed to drag-induced underbody, rear side, and the opposite side of the wind attack. The car's power requirement increased significantly with side wind, potentially causing instability in high winds exceeding 15 m/s. However, at no wind effect, the drag force of the variant with a clustered battery pack decreased by 7.15%. The implemented methodology for sizing and packaging the BEV powertrain resulted total reduction of battery size by 7.23 kWh. The study further evaluated the ride dynamic performance of a converted car using MATLAB/SIMULINK software. While no significant changes in comfort were observed, there was an increase in vertical displacement peak and pitch motions due to center of gravity (CG) position changes. Acceleration over a bump profile ranged from 0.6 to 0.9 m/s2, with discomfort less than 0.315 m/s2. However, no major consequences were observed for a short duration. Finally, the methodology demonstrated its capability in sizing BEV powertrains based on typical driving cycles, vehicle dynamics characteristics, and customer needs.