Shankar Venugopal

Mahindra Group (India)

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Bhanu Pratap

Indian Institute of Technology Madras

T. V. Krishna Mohan

University of Exeter

R. K. Amit

Indian Institute of Technology Madras

Varada Prashant Rao

Aditya Ramji

University of California, Davis

Mithileysh Sathiyanarayanan

University of London

Spurthi Ravuri

Center for Study of Science Technology and Policy

V. Ramachandran

Indian Institute of Technology Madras

Srinivas Gunti

Indian Institute of Technology Madras

Surendranath Mutta

Mahindra Group (India)

Cooperative Institutions

Mahindra Group (India)

Indian Institute of Technology Madras

Indian Institute of Science Bangalore

Center for Study of Science Technology and Policy

Indian Institute of Technology Indore

Indian Institute of Technology Kanpur

University of California, Davis

Energy and Resources Institute

University of London

Christ University

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Analyzing the Impact of Lithium-Ion Battery Recovery Strategy on e-Mobility Revolution

Bhanu Pratap T. V. Krishna Mohan R. K. Amit Shankar Venugopal

10.1109/itec-india59098.2023.10471418

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Model Based Road Slope and Mass Estimation of Road Vehicles

2017 IEEE Transportation Electrification Conference (ITEC-India) (2021)

Surendranath Mutta Shankar C. Subramanian Srinivas Gunti Mithileysh Sathiyanarayanan Shankar Venugopal

Performance, fuel economy, driving experience, and safety are the most critical attributes automotive original equipment manufacturers (OEMs) focus on meeting customer requirements. OEMs are coming up with many features content to meet the customer requirements while meeting the stringent regulations regarding emissions and safety. Advanced sensors and embedded controllers are employed to meet the above needs. Performance of these algorithms can be significantly improved if we accurately predict a few important vehicle operational parameters. Vehicle mass and road slope are two crucial parameters essential for developing and optimizing control algorithms of powertrain, brake, and advanced driver assistance systems (ADAS). This study focuses on model-based road slope and vehicle mass estimation by integrating a state estimation algorithm and a longitudinal dynamics model. Drive-train torque, vehicle velocity, and vehicle design parameters are inputs for developing a longitudinal dynamics model. Initial approximate estimates of road slope and vehicle mass are given as initialization values for the state estimation algorithm, and future estimates are obtained using recursive adaptive filtering. A comparative study was performed between Extended Kalman filter (EKF) and Recursive Least Square (RLS) estimation algorithms for the convergence rate of state variables and error with respect to the actual state.

Initialization

Original equipment manufacturer

Powertrain

10.1109/itec-india53713.2021.9932461

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Making EVs Profitable : Design for Value and Cost through smart architecting

2017 IEEE Transportation Electrification Conference (ITEC-India) (2019)

Varada Prashant Rao Shankar Venugopal

The Future of sustainable Mobility is being shaped by trends towards Connected, Autonomous, Shared, Electric (CASE) vehicle technologies. To accelerate the transition from the Internal Combustion Engines (ICEs) Vehicles to Electric Vehicles (EVs), we need to design and offer EVs that have (a) low total cost of operation (TCO), (b) low product - lifecycle cost and (c) high environmental sustainability. The objective of the paper is to demonstrate two strategies of Design to Value (DTV) and Design to Cost (DTC) can enable this transition. The paper suggests methods and opportunities to increase value and reduce cost for native EV Architecture based on innovative design and platform strategy.

Sustainable Design

10.1109/itec-india48457.2019.itecindia2019-249

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Pragmatic Model-Based Design approach to accelerate and scale the EV Skills development

R Vijayalayan Rashmi Rao Shankar Venugopal

10.1109/itec-india59098.2023.10471505

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IP and Innovation Strategy for Developing Next-Generation Automotive Technologies

SAE technical papers on CD-ROM/SAE technical paper series (2015)

Ajay Joshi Shankar Venugopal

10.4271/2015-26-0071

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Visualizing the complex demand and supply dynamics of critical battery materials—a key enabler for realizing the Electric Mobility Vision 2030

2017 IEEE Transportation Electrification Conference (ITEC-India) (2019)

Bhanu Pratap T. V. Krishna Mohan R. K. Amit Shankar Venugopal

To achieve the 'Zero emission mandate', India put forward the Electric Mobility Vision 2030 which aims that in 2030, Electric vehicles will contribute around 30% of total automobile sales. Uncertainty in the availability of battery raw materials and lack of battery manufacturing facility can be the bottlenecks in achieving the Vision 2030. In this paper, we develop a system dynamics model to analyze the effect of complex demand and supply dynamics of critical battery materials in the avenue of Electric Mobility Vision 2030. Our study indicates that fluctuations in the price of key battery materials—Lithium and Cobalt—can be a major deterrent in realizing the Vision 2030. Hence we need to model and predict the Demand vs. Supply dynamics so that we can take proactive steps towards mitigating the supply risks and realize the vision.

Enabling

Mandate

10.1109/itec-india48457.2019.itecindia2019-170

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Powering the Future: Harnessing an Ecosystem Approach to Drive Electric Vehicle Adoption

Spurthi Ravuri Thirumalai NC Shankar Venugopal

10.1109/itec-india59098.2023.10471426

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A Road Map to Sustainable Mobility: Analyzing the Dynamics of Lithium-Ion Battery Recycling

2017 IEEE Transportation Electrification Conference (ITEC-India) (2021)

T. V. Krishna Mohan Bhanu Pratap R. K. Amit Shankar Venugopal

Lithium-ion batteries are the primary power source of electric vehicles. The uncertainty in the availability of raw materials for LIB increases the significance of recycling. This research presents a system dynamics model that represents the dynamics of the lithium-ion battery recycling ecosystem. Our study indicates that the reuse of lithium-ion batteries for stationary storage applications will limit their availability for recycling and mobility applications. But, these LIBs can be reused for stationary storage applications for renewable energy production. Thus, achieving the Electric Mobility vision 2030 may also enable the achievement of renewable energy capacity targets for 2030.

Lithium iron phosphate

10.1109/itec-india53713.2021.9932513

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Enhanced Technical Capability for EV and SDV through AI based Functional Competency Assessment

Shekhar Malani Javed Inamdar Shankar Venugopal

10.1109/itec-india59098.2023.10471437

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Design of Lightweight Composites for Vehicle Front End Energy Management of Bumper Beam

SAE technical papers on CD-ROM/SAE technical paper series (2019)

Praveen Kumar Sarma S. R. Akella Ayan Chakraborty Balasubramanian Muthiah V. Ramachandran

10.4271/2019-28-0085

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