Ricardo de Castro

Driving coach: A smartphone application to evaluate driving efficient patterns

In spite of several technical advances made in recent years by the automotive industry, the drivers behaviour still influences significantly the overall fuel consumption. With the rise of smartphones adoption, there are also new opportunities to increase the awareness to this issue. The main aim of this paper is to present a new smartphone application that will help drivers reduce the fuel consumption of their vehicles. This is accomplished by using the smartphones sensors and the vehicle state to detect the driving pattern and suggest new behaviours in real time that will lead to a more efficient driving experience. The preliminary results show the potential for significant energy savings and their relevance for changing the drivers behaviour.

Torque blending and wheel slip control in EVs with in-wheel motors

Among the many opportunities offered by electric vehicles (EVs), the design of power trains based on in-wheel electric motors represents, from the vehicle dynamics point of view, a very attractive prospect, mainly due to the torque-vectoring capabilities. However, this distributed propulsion also poses some practical challenges, owing to the constraints arising from motor installation in a confined space, to the increased unsprung mass weight and to the integration of the electric motor with the friction brakes. This last issue is the main theme of this work, which, in particular, focuses on the design of the anti-lock braking system (ABS). The proposed structure for the ABS is composed of a tyre slip controller, a wheel torque allocator and a braking supervisor. To address the slip regulation problem, an adaptive controller is devised, offering robustness to uncertainties in the tyre–road friction and featuring a gain-scheduling mechanism based on the vehicle velocity. Further, an optimisation framework is employed in the torque allocator to determine the optimal split between electric and friction brake torque based on energy performance metrics, actuator constraints and different actuators bandwidth. Finally, based on the EV working condition, the priorities of this allocation scheme are adapted by the braking supervisor unit. Simulation results obtained with the CarSim vehicle model, demonstrate the effectiveness of the overall approach.

Optimal sizing and energy management of hybrid storage systems

This paper targets the development of hybrid energy storage systems (ESS), based on the batteries-supercapacitors blending. In particular, we will develop two methodologies for the combined sizing/energy management of hybrid ESS. The first method assumes that the division of power between the sources is performed through low/high pass filters, which allow us to evaluate, in a simple and rapid way, the trade-offs and economic gains due to the hybridization. The second approach relies on a nonlinear optimization problem, and seeks the minimization of the installation and electrical charging costs of the sources. Simulation results reveal the existence of a threshold in the EV range, from which the introduction of the supercapacitors is less beneficial in economic terms.

DC link control for multiple energy sources in electric vehicles

In this paper, a detailed description of a control architecture for managing the DC link control of EVs with multiple energy sources is presented. The proposed topology allows the control of the power flow among supercapacitors and batteries, while ensuring the regulation of the DC link voltage, thanks to a cascade of voltage and current linear controllers. A simple analytical study is provided to illustrate the tuning guidelines for the current and voltage, based on proportional + integral controllers. A prototype system has been designed and built in reduced scale hardware to analyze the performance of the proposed control system. The experimental results are in accordance with the simulations and demonstrated the effectiveness of the proposed control technique.

Minimum-time Manoeuvring in Electric Vehicles with Four Wheel-Individual-Motors

The coordinated control of vehicle actuators is gaining more and more importance as new platforms are becoming available, with chassis endowed with many different actuators that may help controlling the vehicle motion. Furthermore, wheel individual motors allow using a single system to apply both positive and negative torques at the wheels, which can be actuated independently one from the other. In electric vehicles (EVs), moreover, such a freedom in the actuation mechanisms opens the way to the combined optimisation of performance and energy consumption issues. In this paper, the problem of minimum-time manoeuvring in EVs is addressed, and the proposed strategy is compared against a benchmark, a-causal optimal solution showing that only a negligible loss of performance is experienced.

A model predictive control allocation approach to hybrid braking of electric vehicles

With the recent emergence of electric drivetrains, a faster and energy efficient braking actuator the electric motor has become available to complement the operation of the traditional friction brakes. The decision on how to split the braking torque among the friction brake and the electric motor is one of the main issues of such hybrid braking systems. With this challenge in mind, a new model predictive control allocation (MPCA) approach for hybrid braking is proposed. In comparison to state of the art torque blending solutions (daisy chain and dynamic control allocation) the MPCA offers faster transient response, without compromising the energy recuperation efficiency of the actuators. In addition, we also develop a linear wheel slip controller to regulate the braking force during emergency braking maneuvers. The tuning of this wheel slip controller is carried out using robust pole placement techniques, which ensures good operation in spite of uncertainties in the tire-road friction coefficient and the vertical load. Simulation results demonstrate the effectiveness of the proposed method.

Design of safety-oriented control allocation strategies for overactuated electric vehicles

The new vehicle platforms for electric vehicles (EVs) that are becoming available are characterised by actuator redundancy, which makes it possible to jointly optimise different aspects of the vehicle motion. To do this, high-level control objectives are first specified and solved with appropriate control strategies. Then, the resulting virtual control action must be translated into actual actuator commands by a control allocation layer that takes care of computing the forces to be applied at the wheels. This step, in general, is quite demanding as far as computational complexity is considered. In this work, a safety-oriented approach to this problem is proposed. Specifically, a four-wheel steer EV with four in-wheel motors is considered, and the high-level motion controller is designed within a sliding mode framework with conditional integrators. For distributing the forces among the tyres, two control allocation approaches are investigated. The first, based on the extension of the cascading generalised inverse method, is computationally efficient but shows some limitations in dealing with unfeasible force values. To solve the problem, a second allocation algorithm is proposed, which relies on the linearisation of the tyre–road friction constraints. Extensive tests, carried out in the CarSim simulation environment, demonstrate the effectiveness of the proposed approach.

Influence of Li-Ion Battery Models in the Sizing of Hybrid Storage Systems with Supercapacitors

This paper presents a comparative study of the influence of different aggregated electrical circuit battery models in the sizing process of a hybrid energy storage system (ESS), composed by Li-ion batteries and supercapacitors (SCs). The aim is to find the number of cells required to propel a certain vehicle over a predefined driving cycle. During this process, three battery models will be considered. The first consists in a linear static zeroeth order battery model over a restricted operating window. The second is a non-linear static model, while the third takes into account first- order dynamics of the battery. Simulation results demonstrate that the adoption of a more accurate battery model in the sizing of hybrid ESSs prevents over-sizing, leading to a reduction in the number of cells of up to 29%, and a cost decrease of up to 10%.

Adaptive-Robust Friction Compensation in a Hybrid Brake-by-Wire Actuator

This work focuses on the development of a pressure-loop controller for a hybrid brake-by-wire system, composed of a hydraulic link and an electro-mechanical actuator. Towards this goal, we will start by constructing a reduced model that is capable of capturing the fundamental dynamics of the actuator, which is particularly useful for control design purposes. Motivated by the large friction disturbances that affect the system, we also investigate linear-in-the-parameter models suitable for (online) model-based friction compensation. More specifically, results from the theory of function approximation, together with optimization techniques, are explored to approximate the Stribeck friction model through a linear-in-the-parameter model. This new linear-in-the-parameter model is then employed in the design of a control law for tracking the braking pressure of the hybrid brake-by-wire. The main features of this controller are the robustness to parametric uncertainties, thanks to the inclusion of a switching-σ adaptive mechanism, and the attenuation of non-parametric disturbances with a continuous sliding mode action. The stability and robustness properties of the closed-loop system are investigated with the help of the Lyapunov method. Finally, experimental tests demonstrate the effectiveness of the proposed approach and its ability to handle disturbances.

A control allocation approach to manage multiple energy sources in EVs

This article is concerned with the design of an energy management system (EMS) for the hybridization of multiple energy sources (ESs) in electric vehicles, focusing in a particular configuration composed by batteries and supercapacitors (SCs). As a first design step, we investigated an (non-causal) optimal power allocation, targeting the minimization of the energy losses over a complete driving cycle. Albeit the solution obtained with this formulation demands the advance knowledge of the vehicle driving cycle, it also provides a useful benchmark solution to assess the performance of causal EMSs. A more practical EMS is then derived, based on the control allocation (CA) concept. This approach, typically employed in redundant control systems, enable us to address the various objectives and constraints that appear in EMS design problem, such as the DC bus voltage regulation, SC state of charge tracking, minimization of power losses, current and state of charge limits, etc. Simulation results show the effectiveness of the proposed CA based EMS, yielding performances very close to the optimal non-causal power allocation.