Optimal Longitudinal Slip Ratio Allocation and Control of a Hybrid Electric Vehicle With eAWD Capabilities

2016 ◽  
Author(s):  
Jose Velazquez Alcantar ◽  
Francis Assadian ◽  
Ming Kuang ◽  
Eric Tseng
Keyword(s):  
Control System ◽  
Electric Vehicle ◽  
Optimization Algorithm ◽  
Hybrid Electric Vehicle ◽  
Rear Axle ◽  
Surface Condition ◽  
Road Surface ◽  
Slip Ratio ◽  
Hybrid Electric ◽  
Longitudinal Slip

This paper introduces a Hybrid Electric Vehicle (HEV) with eAWD capabilities via the use of a traditional Series-Parallel hybrid transaxle at the front axle and an electric Rear Axle Drive (eRAD) unit at the rear axle. Such a vehicle requires proper wheel torque allocation to the front and rear axles in order to meet the driver demands. A model of the drivetrain is developed using Bond Graphs and is used in co-simulation with a vehicle model from the CarSim software suite for validation purposes. A longitudinal slip ratio control architecture is proposed which allocates slip ratio to the front and real axles via a simple optimization algorithm. The Youla parametrization technique is used to develop robust controllers to track the optimal slip targets generated by the slip ratio optimization algorithm. The proposed control system offers a unified approach to longitudinal vehicle control under both traction and braking events under any road surface condition. It is shown in simulation that the proposed control system can properly allocate slip ratio to the front and rear axles such that tires remain below their force saturation limits while vehicle acceleration/braking is maximized while on a low friction road surface.

Vehicle Dynamics Control of eAWD Hybrid Electric Vehicle Using Slip Ratio Optimization and Allocation

2018 ◽  
Vol 140 (9) ◽  
Author(s):  
Jose Velazquez Alcantar ◽  
Francis Assadian ◽  
Ming Kuang
Keyword(s):  
Control System ◽  
Hybrid Electric Vehicle ◽  
Rear Axle ◽  
Total Power ◽  
Slip Ratio ◽  
Handling Characteristics ◽  
Wheel Drive ◽  
Torque Vectoring ◽  
Hybrid Electric ◽  
Ratio Optimization

Hybrid electric vehicles (HEV) offer improved fuel efficiency compared to their conventional counterparts at the expense of adding complexity and at times, reduced total power. As a result, HEV generally lack the dynamic performance that customers enjoy. To address this issue, the paper presents a HEV with electric all-wheel drive (eAWD) capabilities via the use of a torque vectoring electric rear axle drive (TVeRAD) unit to power the rear axle. The addition of TVeRAD to a front wheel drive HEV improves the total power output. To further improve the handling characteristics of the vehicle, the TVeRAD unit allows for wheel torque vectoring (TV) at the rear axle. A bond graph model of the proposed drivetrain model is developed and used in cosimulation with carsim. The paper proposes a control system, which utilizes slip ratio optimization to allocate control to each tire. The optimization algorithm is used to obtain optimal slip ratio targets to at each tire such that the targets avoid tire saturation. The Youla parameterization technique is used to develop robust tracking controllers for each axle. The proposed control system is ultimately tested on the drivetrain model with a high fidelity carsim vehicle model for validation. Simulation results show that the control system is able to maximize vehicle longitudinal performance while avoiding tire saturation on a low μ surface. More importantly, the control system is able to track the desired yaw moment request on a high-speed double-lane change (DLC) maneuver through the use of the TVeRAD to improve the handling characteristic of the vehicle.

scholarly journals A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3147
Author(s):  
Kiyoung Kim ◽  
Namdoo Kim ◽  
Jongryeol Jeong ◽  
Sunghwan Min ◽  
Horim Yang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Electric Vehicle ◽  
Optimization Algorithm ◽  
Hybrid Electric Vehicle ◽  
New Technologies ◽  
New Technology ◽  
Dynamic Performance ◽  
Minimum Principle ◽  
Component Sizing ◽  
Hybrid Electric

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

Development of a Clutch Control System for a Hybrid Electric Vehicle with One Motor and Two Clutches

2011 ◽  
Vol 44 (1) ◽  
pp. 4797-4802 ◽  
Author(s):  
Kazutaka Adachi ◽  
Hiroyuki Ashizawa ◽  
Sachiyo Nomura ◽  
Yoshimasa Ochi
Keyword(s):  
Control System ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric ◽  
Clutch Control
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