By Joseph Shore 
Tribology Division

Range anxiety remains a key barrier to the widespread adoption of electric vehicles (EVs). To maximise range, automotive manufacturers are increasingly focusing on improving the efficiency of mechanical components. In comparison to an internal combustion engine (ICE), typically limited to around 40% efficiency, the efficiency of an electric motor may exceed 90% [1,2]. As a result, other sources of losses, such as those in the transmission, comprise a much more significant proportion of overall power losses in an EV than they do in an ICE vehicle, thus the optimisation of transmission design and lubricants provides an important avenue for improving vehicle range.

At Imperial, we have developed a new model for predicting transmission power losses and assessing the influence of modifying transmission design parameters on overall system efficiency over an entire representative drive cycle.

The primary sources of power losses in a gearbox are gear meshing friction, churning of the lubricant by the gears, and losses in the bearings and seals. There are often competing requirements for lubricant properties for reducing each of these sources of losses. For example, whilst reducing lubricant viscosity may help to reduce gear churning losses at high speeds, it will also reduce the thickness of the lubricant film between a pair of meshing gear teeth, increasing metal-to-metal contact and thus gear friction at lower speeds. Assessing these competing requirements is further complicated by the inherently transient nature of a vehicles operation; the transmission fluid will heat up and cool down over the course of a drive cycle, resulting in changes in the lubricant properties and hence the power losses at subsequent time steps. It is imperative to predict this evolution in temperature alongside power losses when assessing system performance.

This model predicts gear friction with an iterative scheme which accounts for measured lubricant rheology, allowing for nominally similar lubricants to be evaluated in terms of their influence on efficiency. Bearing and seal losses are predicted using existing models, and gear churning losses are predicted with a newly developed regression equation. The thermal coupling between the losses and the resultant evolution of gearbox temperatures is accounted for using a thermal network approach; the transmission is discretised into a network of temperature nodes, with the relationship between each of these being estimated with empirical heat transfer solutions. This network is solved at each time step within the cycle, updating the temperatures for the subsequent step. The approach accounts for temperatures changes resulting from power losses in the transmission, additional heat from the motor, and cooling via a heat exchanger. The model was validated with a series of road tests on a real EV. The vehicle’s transmission was instrumented with thermocouples situated as to be representative of some if the thermal network’s nodes. The initial temperatures and the vehicles’ speed and torque were then inputted into the model and the predicted temperature evolution was compared to the measurements, showing excellent agreement.

The model provides a means to quickly assess the effects of changing a lubricant property or the transmission design on transmission efficiency. A parameter study was conducted on lubricant viscosity for several drive cycles. Results showed that the optimal viscosity in terms of transmission power losses was significantly higher in a low-speed cycle with frequent start-stops, representative of city driving, than in a higher speed cycle more representative of motorway driving. In the former case, a higher viscosity fluid helps to reduce gear friction during start-stop conditions, whereas a lower viscosity fluid helps to reduce gear churning losses at motorway speeds.

Read more:  

  • Albatayneh, Aiman, et al. "Comparison of the overall energy efficiency for internal combustion engine vehicles and electric vehicles." Rigas Tehniskas Universitates Zinatniskie Raksti1 (2020): 669-680.