Tribological Performance of Green Lubricants Under EMF Applied to Electric Vehicles Mobility

Electric/hybrid vehicles (EVs/HEVs) are gaining increased attention and operate on electric motors. The role of lubricant in e-motor is to provide lubrication, thermal management and material adaptability with elastomers/polymers are among the most important concerns.  The operating conditions

Project Title

Tribological Performance of Green Lubricants Under EMF Applied to Electric Vehicles Mobility

Project Area of Specialization

Mechanical Engineering

Project Summary

Electric/hybrid vehicles (EVs/HEVs) are gaining increased attention and operate on electric motors. The role of lubricant in e-motor is to provide lubrication, thermal management and material adaptability with elastomers/polymers are among the most important concerns.  The operating conditions for EV are tough and may find high temperatures (above 180oC), high operating speed (above 2500rpm), magnetic field condition, more oxidation, more copper corrosion in windings, and abrasion of particles.

To achieve such protection, it is essential to design the lubricant with proper tribological and rheological properties, a base oil is extracted from cotton seeds, obtained from local suppliers. A two-step catalyzed transesterification is used to synthesize the crude cottonseed oil to form bio-diesel and then chemically refined to obtain bio-lubricant. Multiple nano-particles have been used and synthesized with base oil to form hybrid nanofluids.

The test fixture is developed to generate magnetic field conditions on pin-on-disc tribometer and a series of tests will be performed to measure the tribological properties under different operating conditions. The input variables are load, speed, temperature, and concentration of nano-particles and the output is coefficient of friction (CoF).

This present project includes the design of a new lubricant using an artificial neural network (ANN) and a genetic algorithm (GA). Experimentally generated data is used for the artificial neural network (ANN) to train the model and subsequently validate the model. Whereas, a genetic algorithm (GA) is used for optimization using ANN models as the objective function.

Project Objectives

Aims and Objectives

• Pin-on-Disc Tribometer Testing
• Specimen Preparation, Polishing
• Preparation of hybrid nano-fluids
• Magnetic Field Activation and Measurement of Magnetic field Strength
• Thermal & Mechanical Properties of Oils (k, Cp, Viscosity, Density,)
• Wear Measurement & COF Measurement
• Surface Roughness Measurement(Before & After Test)
• SEM, XRD, TIM for surface characterization
• Development of artificial neural network (ANN) by using experimental data
• Specify optimized concentration of nano-particles for better performance through a genetic algorithm.

Project Implementation Method

Preparation of Bio-Lubricant by two-step Transesterification process followed by vacuum distillation

Preparation of hybrid nano-fluid

Manufacturing of tribo-pair(pins and Disc)

Surface Characterization of tribo-pair before testing.

Testing of hybrid nano-fluid under magnetic field condition

Surface Characterization of tribo-pair after testing.

Physico-chemical properties of nano-fluid

Benefits of the Project

Contribute to e-mobility advancement by using latest development in data science

Environmentally friendly lubricant for electric/hybrid vehicles

Low energy loss in electric vehicle electric/hybrid motor operations in severe conditions

Less wear because of the low viscosity of the green lubricant 

Better thermal management for electric/hybrid vehicle electric motors 

Technical Details of Final Deliverable

Generation of ANN model in MATLAB and optimization of green lubricant by genetic algorithm.

The mathematical model for lubricant design

Optimized concentration of nano-particles with ANN model

Quantify the reduction in CoF and compare it with the ANN model

Wear scar measurements on tribo-pair bodies

Viscosity variations w.r.t to temperature under different lubrication regimes

Final Deliverable of the Project

Hardware System

Core Industry

Transportation

Other Industries

Petroleum , Energy

Core Technology

Others

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

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