Vehicle Dynamics Control to Enhance Energy Efficiency and Safety of Electric and Hybrid Vehicles

Special Issue Editors


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Guest Editor
Centre for Automotive Engineering, University of Surrey, Guildford, UK
Interests: modelling of vehicle systems; high and low level vehicle control strategies design; vehicle state estimation; vehicle testing, data acquisition and analysis; on- and off-road vehicle dynamics; optimal control

Special Issue Information

Dear Colleagues,

Electric and hybrid vehicles have emerged as game-changers in the automotive industry, addressing the pressing need for sustainable and eco-friendly transportation solutions. Efficient energy management plays a pivotal role in enhancing the range and performance of electric and hybrid vehicles, and sophisticated algorithms and optimization techniques are being developed to intelligently distribute power, minimize energy losses, and extend the driving range. While energy efficiency is a primary concern, safety remains paramount in the development of electric and hybrid vehicles. As these become more sophisticated, incorporating advanced driver-assistance systems and automated driving capabilities, ensures a safe and reliable operation is essential.

This Special Issue focuses on vehicle dynamics control technologies for both electric and hybrid vehicles. The focus of this Special Issue is on vehicle control strategies, targeting the following topics: (i) reduction in energy consumption; (ii) improvement of vehicle stability and therefore safety; (iii) maximization of tractive performance; and (iv) component preservation and driver comfort. This Special Issue will cover vehicle topologies including electric centralized powertrains as well as distributed motors, standalone or in combination with internal combustion engines. The integration of additional smart actuators (e.g., active differentials, active suspensions, brake-by-wire, steer-by-wire) to the electric/hybrid propulsion system is also contemplated and adds challenges in terms of controller integration and/or co-existence with other systems. The considered domains include the following: optimization, modeling, numerical simulations, hardware/driver-in-the-loop, real-time implementation and experimental testing, and vehicle control for both human-driven and automated vehicles.

We encourage researchers, academics, and industry professionals to contribute to this Special Issue by submitting their original and innovative research work.

Topics of interest include, but are not limited to, the following:

  • Intelligent control techniques for energy recovery including regenerative braking, and energy-efficient cruise control.
  • Safety-enhancing control strategies for electric and hybrid vehicles exploiting the distributed electric machines and the additional smart actuators.
  • Traction control algorithms to enhance tractive performance and guarantee steerability.
  • Anti-jerk control function to preserve vehicle components and enhance driver comfort.
  • Integration of control systems with emerging technologies, such as artificial intelligence, machine learning, and V2X.

Dr. Davide Tavernini
Prof. Dr. Basilio Lenzo
Guest Editors

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Keywords

  • energy efficiency
  • torque vectoring
  • traction
  • electric vehicles
  • electric motors
  • vehicle control
  • anti-jerk

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Published Papers (2 papers)

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Research

26 pages, 2702 KiB  
Article
Simultaneous Optimisation of Vehicle Design and Control for Improving Vehicle Performance and Energy Efficiency Using an Open Source Minimum Lap Time Simulation Framework
by Alberto Jiménez Elbal, Adrián Zarzuelo Conde and Efstathios Siampis
World Electr. Veh. J. 2024, 15(8), 366; https://doi.org/10.3390/wevj15080366 - 13 Aug 2024
Viewed by 906
Abstract
This paper presents a comprehensive framework for optimising vehicle performance, integrating advanced simulation techniques with optimisation methodologies. The aim is to find the best racing line, as well as the optimal combination of parameters and control inputs to make a car as fast [...] Read more.
This paper presents a comprehensive framework for optimising vehicle performance, integrating advanced simulation techniques with optimisation methodologies. The aim is to find the best racing line, as well as the optimal combination of parameters and control inputs to make a car as fast as possible around a given track, with a focus on energy deployment and recovery, active torque distribution and active aerodynamics. The problem known as the Minimum Lap Time Problem is solved using optimal control methods and direct collocation. The solution covers the modelling of the track, vehicle dynamics, active aerodynamics, and a comprehensive representation of the powertrain including motor, engine, transmission, and drivetrain components. This integrated simulator allows for the exploration of different vehicle configurations and track layouts, providing insights into optimising vehicle design and vehicle control simultaneously for improved performance and energy efficiency. Test results demonstrate the effect of active torque distribution on performance under various conditions, enhanced energy efficiency and performance through regenerative braking, and the added value of including parameter optimisation within the optimisation framework. Notably, the simulations revealed interesting behaviours similar to lift-and-coast strategies, depending on the importance of energy saving, thereby highlighting the effectiveness of the proposed control strategies. Also, results demonstrate the positive effect of active torque distribution on performance under various conditions, attributed to the higher utilization of available adherence. Furthermore, unlike a simpler single-track model, the optimal solution required fine control of the active aerodynamic systems, reflecting the complex interactions between different subsystems that the simulation can capture. Finally, the inclusion of parameter optimisation while considering all active systems, further improves performance and provides valuable insights into the impact of design choices. Full article
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13 pages, 771 KiB  
Article
Impact of Engine Inertia on P2 Mild HEV Fuel Consumption
by Gulnora Yakhshilikova, Sanjarbek Ruzimov, Andrea Tonoli and Akmal Mukhitdinov
World Electr. Veh. J. 2024, 15(5), 220; https://doi.org/10.3390/wevj15050220 - 19 May 2024
Cited by 1 | Viewed by 1094
Abstract
The energy management system (EMS) of a hybrid electric vehicle (HEV) is an algorithm that determines the power split between the electrical and thermal paths. It defines the operating state of the power sources, i.e., the electric motor (EM) and the internal combustion [...] Read more.
The energy management system (EMS) of a hybrid electric vehicle (HEV) is an algorithm that determines the power split between the electrical and thermal paths. It defines the operating state of the power sources, i.e., the electric motor (EM) and the internal combustion engine (ICE). It is therefore one of the main factors that can significantly influence the fuel consumption and performance of hybrid vehicles. In the transmission path, the power generated by the ICE is in part employed to accelerate the rotating components of the powertrain, such as the crankshaft, flywheel, gears, and shafts. The main inertial components are the crankshaft and the flywheel. This additional power is significant during high-intensity acceleration. Therefore, the actual engine operation is different from that required by the power split unit. This study focuses on exploring the influence of engine inertia on HEV fuel consumption by developing a controller based on an equivalent consumption minimisation strategy (ECMS) that considers crankshaft and flywheel inertia. The optimal solution obtained by the ECMS controller is refined by incorporating the inertia effect of the main rotating components of the engine into the cost function. This reduces the engine operation during high inertial torque transient phases, resulting in a decrease in vehicle CO2 emissions by 2.34, 2.22, and 1.13 g/km for the UDDS, US06, and WLTC driving cycles, respectively. Full article
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