A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed

A Real-time Nonlinear Model Predictive Controller for Yaw Motion Optimization of Distributed Drive Electric Vehicles

This paper proposes a real-time nonlinear model predictive control (NMPC) strategy for direct yaw moment control (DYC) of distributed drive electric vehicles (DDEVs). The NMPC strategy is based on a control-oriented model built by integrating a single track vehicle model with the Magic Formula (MF) tire model. To mitigate the NMPC computational cost, the continuation/generalized minimal residual (C/GMRES) algorithm is employed and modified for real-time optimization. Since the traditional C/GMRES algorithm cannot directly solve the inequality constraint problem, the external penalty method is introduced to transform inequality constraints into an equivalently unconstrained optimization problem. Based on the Pontryagin’s minimum principle (PMP), the existence and uniqueness for solution of the proposed C/GMRES algorithm are proven. Additionally, to achieve fast initialization in C/GMRES algorithm, the varying predictive duration is adopted so that the analytic expressions of optimally initial solutions in C/GMRES algorithm can be derived and gained. A Karush-Kuhn-Tucker (KKT) condition based control allocation method distributes the desired traction and yaw moment among four independent motors. Numerical simulations are carried out by combining CarSim and Matlab/Simulink to evaluate the effectiveness of the proposed strategy. Results demonstrate that the real-time NMPC strategy can achieve superior vehicle stability performance, guarantee the given safety constraints, and significantly reduce the computational efforts

Power loss minimization in electric cars by wheel force allocation

The need for lowering the emission levels has never been greater than now. In the vehicle industry, electrification seems to be an irreversible way ahead but user-related challenges such as limited range delay electricity as the primary energy source for personal transportation. Other control-related challenges are also introduced as electric cars are over-actuated, i.e. several actuators can be used for the same purpose. Over-actuation introduces the possibility to choose more freely which actuator to use when. Can this freedom of choice be used to improve energy efficiency of electric cars by e.g. minimizing power losses? In this thesis, two wheel force distribution algorithms have been developed with a method called control allocation. The algorithms minimize power losses in the electric drivetrain, transmission and tires. They were tested in a simulated city cycle in a Volvo V60 configuration with four electric motors, each connected to a wheel through a single speed transmission and coupling respectively. It was found that by using developed algorithms, up to 3.9% energy could be saved. In a next step, the transmission ratio on the front motors and rear motors were optimized in combination with one of the algorithms. By using a larger transmission ratio in the front than in the rear, the energy consumption reduced even further. With these development steps, up to 7.9% energy could be saved compared to the original vehicle

A fast and parametric torque distribution strategy for four-wheel-drive energy-efficient electric vehicles

Electric vehicles (EVs) with four individually controlled drivetrains are over-actuated systems, and therefore, the total wheel torque and yaw moment demands can be realized through an infinite number of feasible wheel torque combinations. Hence, an energy-efficient torque distribution among the four drivetrains is crucial for reducing the drivetrain power losses and extending driving range. In this paper, the optimal torque distribution is formulated as the solution of a parametric optimization problem, depending on the vehicle speed. An analytical solution is provided for the case of equal drivetrains, under the experimentally confirmed hypothesis that the drivetrain power losses are strictly monotonically increasing with the torque demand. The easily implementable and computationally fast wheel torque distribution algorithm is validated by simulations and experiments on an EV demonstrator, along driving cycles and cornering maneuvers. The results show considerable energy savings compared to alternative torque distribution strategies

Energy reduction by power loss minimisation through wheel torque allocation in electric vehicles: a simulation-based approach

As vehicles become increasingly electrified, electrical machines for propulsion can be divided into many sources making the vehicle highly over-actuated. For over-actuated vehicles, the allocation of a propulsive force is an underdetermined process with respect to both the number of wheels and electrical machines. Hence, the allocation can be made to favour particular attributes such as energy consumption. In this study, a vehicle equipped with four identical electric motors with a fixed transmission ratio connected through a half-shaft and a coupling to one wheel respectively is driven a 2-h-long city cycle in the vicinity of G\uf6teborg. Two different control allocation methods are presented to distribute torque momentaneously based on driver request while minimising power losses in electric motor and inverter as well as tyres. One method is a quadratic programming optimisation and the other is an offline exhaustive search method resulting in a look-up table based on requested torque and actual speed. The two methods are compared to other torque distribution strategies based on fixed distribution ratio and equal tyre-to-road friction utilisation. It was found that using the developed optimisation algorithms, a reduction of up to 3.9% in energy consumption can be obtained

Energy efficient torque vectoring control

Tire forces are at the heart of the dynamic qualities of vehicles. With the advent of electric vehicles the precise and accurate control of the traction and braking forces at the individual wheel becomes a possibility and a reality outside test labs and virtual proving grounds. Benefits of individual wheel torque control, or torque-vectoring, in terms of vehicle dynamics behavior have been well documented in the literature. However, very few studies exist which analyze the individual wheel torque control integrated with vehicle efficiency considerations. This paper focuses on this aspect and discusses the possibilities and benefits of integrated, energy efficient torque vectoring control. Experiments with a four-wheel-drive electric vehicle show that considerable energy savings can be achieved by considering drivetrain and tire power losses through energy efficient torque vectoring control

Energy-efficient torque-vectoring control of electric vehicles with multiple drivetrains

The safety benefits of torque-vectoring control of electric vehicles with multiple drivetrains are well known and extensively discussed in the literature. Also, several authors analyze wheel torque control allocation algorithms for reducing the energy consumption while obtaining the wheel torque demand and reference yaw moment specified by the higher layer of a torque-vectoring controller. Based on a set of novel experimental results, this study demonstrates that further significant energy consumption reductions can be achieved through the appropriate tuning of the reference understeer characteristics. The effects of drivetrain power losses and tire slip power losses are discussed for the case of identical drivetrains at the four vehicle corners. Easily implementable yet effective rule-based algorithms are presented for the set-up of the energy-efficient reference yaw rate, feedforward yaw moment and wheel torque distribution of the torque-vectoring controller

Energy-Optimal Control of Over-Actuated Systems - with Application to a Hybrid Feed Drive

Over-actuated (or input-redundant) systems are characterized by the use of more actuators than the degrees of freedom to be controlled. They are widely used in modern mechanical systems to satisfy various control requirements, such as precision, motion range, fault tolerance, and energy efficiency. This thesis is particularly motivated by an over-actuated hybrid feed drive (HFD) which combines two complementary actuators with the aim to reduce energy consumption without sacrificing positioning accuracy in precision manufacturing. This work addresses the control challenges in achieving energy optimality without sacrificing control performance in so-called weakly input-redundant systems, which characterize the HFD and most other over-actuated systems used in practice. Using calculus of variations, an optimal control ratio/subspace is derived to specify the optimal relationship among the redundant actuators irrespective of external disturbances, leading to a new technique termed optimal control subspace-based (OCS) control allocation. It is shown that the optimal control ratio/subspace is non-causal; accordingly, a causal approximation is proposed and employed in energy-efficient structured controller design for the HFD. Moreover, the concept of control proxy is proposed as an accurate causal measurement of the deviation from the optimal control ratio/subspace. The proxy enables control allocation for weakly redundant systems to be converted into regulation problems, which can be tackled using standard controller design methodologies. Compared to an existing allocation technique, proxy-based control allocation is shown to dynamically allocate control efforts optimally without sacrificing control performance. The relationship between the proposed OCS control allocation and the traditional linear quadratic control approach is discussed for weakly input redundant systems. The two approaches are shown to be equivalent given perfect knowledge of disturbances; however, the OCS control allocation approach is shown to be more desirable for practical applications like the HFD, where disturbances are typically unknown. The OCS control allocation approach is validated in simulations and machining experiments on the HFD; significant reductions in control energy without sacrificing positioning accuracy are achieved.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146104/1/molong_1.pd

MPTC for PMSMs of EVs with Multi-Motor Driven System Considering Optimal Energy Allocation

© 1965-2012 IEEE. This paper presents a compound propulsion system with a high-speed permanent-magnet synchronous motor (PMSM) and two in-wheel motors for electric vehicles (EVs). In this paper, the longitudinal dynamic model of EVs is first presented. Then traction distribution ratio \alpha is introduced to express the traction distribution between the front and the rear axles. Moreover, the function of power consumption concerned with the traction distribution ratio \alpha is established. Therefore, the \alpha that minimizes the power consumption function is selected as the optimal traction distribution ratio. To improve the performance of motor controllers, the model predictive torque control (MPTC) method is employed for high-speed and in-wheel motor drives. Experimental comparison with field-oriented control (FOC) shows the advantages of MPTC in dynamic response. Finally, experimental comparisons and hardware-in-loop (HiL) tests are presented to verify the MPTC method and the proposed energy allocation method, respectively