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Recent Trends on Drivetrain Control Strategies and Battery Parameters of a Hybrid Electric Vehicle
Technical Paper
2019-28-0155
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Environmental consciousness is being developed in each and every sector, automotive industry has concentrated in a greater manner. Reduction of tail pipe emission was concentrated and found that hybridization can ensure better results. Hybrid electric vehicle operates on electric motor as well as internal combustion engine. Battery power is one the major source of energy for driving electric motor and different battery technologies have been developed. Battery management system (BMS) controls battery parameters like State of Charge (SoC), State of Health (SoH) and Depth of Discharge (DoD) which definitely has an impact on power-torque ratings. Various drive train configurations are developed based on the power-torque requirements and size of engine/electric motor. Maintaining proper flow of energy can have better reduction in emissions, more battery life, less fuel consumption and optimum power-torque ratings. Power and torque has to be varied based on the driver’s requirement, maximum power and torque may not be required all the time and that is the area to capitalize some efficiency. Higher fuel efficiency lies in managing energy flow from various power sources to final drive. Energy flow can be controlled by deploying certain logical constraints on battery management system along with drive train which optimises the losses, optimization techniques have shown better results in control of power-torque ratings. This paper explains about the various drive train configurations, battery technologies and their control techniques. Wide range of future scope has been explained by routing each and every technology involved in hybrid vehicles
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Bhaskar, P., Deshmukh, S., Khannan, P., and Shaik, A., "Recent Trends on Drivetrain Control Strategies and Battery Parameters of a Hybrid Electric Vehicle," SAE Technical Paper 2019-28-0155, 2019, https://doi.org/10.4271/2019-28-0155.Data Sets - Support Documents
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