Energy efficient torque allocation design emphasis on payload in a light-duty distributed drive electric vehicle
Open accessAbstract
Light-Duty Electric Vehicle (LDEV) with a distributed drive powertrain provides several potential advantages in terms of flexibility, controllability and responsiveness over conventional powertrains. The precise distribution of driving and braking torque of such configuration is crucially vital for improving the overall performance and efficiency of the vehicles. This paper proposes a new torque allocation (TA) model emphasizing the wheel load variation due to the passenger occupancy payload. A light-duty vehicle model is developed along with the occupancy payload arrangement and a dynamic tire-road friction estimation method for the control system for wheel slip. This proposed TA algorithm uses offline optimization to derive the necessary transmissible torque to the driving wheels. Unlike conventional optimization, it adopts a set of predefined distribution coefficients. Therefore it can execute in a real time platform without high computation power and additional hardware requirements. The efficiency of the model is analyzed using Indian Urban Drive Cycle (IN-UDC). A comparative analysis using a traditional torque allocation model highlights the contributions of this novel torque allocation. The results obtained from various simulations demonstrate the effectiveness of the proposed new TA algorithm.
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In recent years, the demand for electric vehicles (EVs) has accelerated to fulfill worldwide demands of an eco-friendly transportation system.
“In recent years, the demand for electric vehicles (EVs) has accelerated to fulfill worldwide demands of an eco-friendly transportation system [1,2].”
From Electric Vehicle Battery Supply Chain and Critical Materials: A Brief Survey of State of the Art (2023) · cites this paper as [2]
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Self-citation
- Authors
- Barman, P., & Azzopardi, B.
- Affiliations
- Gauhati University (IN)
- Malta College of Arts, Science and Technology (MT)
- Venue
- IEEE Access
- Published
- 2021
- Volume
- 9
- Pages
- 118684-118695
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3193288543
- Cited by
- 15
- References
- 34
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 3 · 2023: 4 · 2022: 4
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- OAR@UM (University of Malta) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- European Commission H2020 TWINNING Networking for Excellence in Electric Mobility Operations (NEEMO) Project (857484)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Keywords
- torque distribution, distributed drive electric vehicles, light-duty electric vehicles, tire-road friction estimation, wheel slip control, offline optimization, real-time control, energy efficiency
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