Transmission speed and ratio optimization for heavy-duty electric truck

Nowadays, the Heavy-Duty Truck industry is facing one of the most critical questions in the universe. How would it be possible to decrease the CO(2) emissions? Performing all possible technological steps in conventional engines is only a “part” of the solution. Electrification is a must for both keeping the environment clean and fulfilling the stringent emission regulations successfully. In this paper, the electrification part of the solution is examined. The main goal is to develop a transmission speed and ratio selection methodology that can be used at the early stages of battery electric truck development, especially for conceptual decisions or hardware selection. The authors are focused on the effect of electric axle (e-axle) transmission speed and ratio selection in 27 Tons Battery Electric (BE) Road Truck application. First of all, a one-dimensional vehicle model is created in GT-Suite software. Then, e-axle, electric motor (e-motor) & battery, regenerative braking model block, electric driveline transmission & differential submodels, and the integrated control algorithm are also implemented. In order to complete a thorough analysis, five different transmission designs (2-speed single, 2 + 1 speed split, 2 + 2 speed split, 3-speed single, 4-speed single) with thousands of gear ratio sets are studied. Satisfying the performance requirements with minimum energy consumption in defined Vecto routes is the vital target of these studies. Dual e-motor studies show that the most effective way of decreasing energy consumption is using e-motors at the same speed (up to 5% benefit) and turning off one (up to 0.6% benefit) below specific torque values if the same e-motors are used. Instead of using complex split transmissions, increasing the number of gears in the single transmission is a prominent configuration because it operates the e-motors at a higher efficient point. In the light of these studies, 3-speed single transmission is capable of providing gradeability requirements with the lowest energy consumption and less system complexity.