Influence of the Final Ratio on the Consumption of an Electric Vehicle under Conditions of Standardized Driving Cycles

Abstract

Electric vehicles must improve their electric drive system efficiency and effectively use their limited energy to become a viable means of transportation. As such, these technologies have undergone substantial improvements from their initial conception. More efficient powertrains, together with improved storage technologies, have enabled more extended autonomy. However, from an engineering perspective, these systems are still a key area of research and optimization. This work presents a powertrain optimization methodology, developing energy savings and improving the performance of the electric vehicle by focusing on the differential. The proposed methodology includes a study of the dynamics of the electric vehicle and the generation of a mathematical model that represents it. By simulating the vehicle and varying the final ratio of the differential, a significant optimization for energy savings is obtained by developing a standardized driving cycle. In this case, NEDC, WLTC-2, and WLTC-3 test cycles are used. The results show that a short ratio improves performance, even if this implies a larger torque from the prime mover. Depending on the operating cycle used, an energy-saving between 3% and 8% was registered. An extended energy autonomy and an increment in the life-cycle of the batteries are expected in real driving scenarios.

Driving Profile Optimization Using a Deep Q‐Network to Enhance Electric Vehicle Battery Life

“…Electric Vehicle Model. When a vehicle moves, it experiences resistance in the direction opposite to the direction of travel, including rolling, air, grade, and inertial resistances; all cause energy loss [28]. The rolling resistance is the energy loss attributable to repeated tire rolls (associated with tire deformation and recovery; Equation (1)):…”

“…The drag force is the principal cause of energy loss. The drag force is horizontal (in the direction opposite of travel) and is caused by shear stress and pressure generated by the vehicle body because of the viscosity of air (Equation ( 3)) [28,29]:…”

Configuration of Electric Vehicles for Specific Applications from a Holistic Perspective

“…Schiffer et al (2017) obtained differences in fuel consumption in diesel-fueled vehicles of 2.0%, 3.2%, and 0.9% for HDDC, NEDC, and WLTP driving cycles, respectively, by modifying the transmission ratios [25]. Similarly, Puma-Benavides et al (2021) obtained energy savings of between 3% and 8% for electric vehicles in NEDC, WLTC-2, and WLTC-3 test cycles by modifying the final ratio of the differential [19]. Total vehicle simulators, such as ADVISOR and FASTSim, have also been used to compare powertrains and estimate the impact of different setups on vehicle efficiency, performance, cost, and battery life [26][27][28].…”

“…Several studies have been carried out to improve the feasibility of implementing electric buses. These include evaluation of different Energy Storage Systems [8][9][10], battery sizing and charging infrastructure [11,12], operational features [13,14], range extenders [15], and powertrain configurations [16][17][18][19][20]. Within the latter strategy, the configuration of electric vehicles is mainly defined by the electric motor, battery, and transmission (if present).…”

“…Based on a total vehicle simulation environment, other studies have considered a holistic approach to the optimization process where gearing parameters are considered omitting the influences of the bearing selection, finding highly relevant results with significantly less effort. Optimizing the transmission ratio to reduce the energy consumption of vehicles is a clear example of this [19,25]. Schiffer et al (2017) obtained differences in fuel consumption in diesel-fueled vehicles of 2.0%, 3.2%, and 0.9% for HDDC, NEDC, and WLTP driving cycles, respectively, by modifying the transmission ratios [25].…”