James Marco

A Novel Method for the Parameterization of a Li-Ion Cell Model for EV/HEV Control Applications

This paper presents a Li-ion cell model parameterization technique for hybrid electric and electric vehicle control applications. The proposed method is based on an equivalent electrical circuit (EEC) model of the Li-ion cell and combines the advantages of the two main strategies employed for cell model parameterization, namely, the offline and online procedures. Offline methods are based on the identification of relevant EEC parameter values using a limited set of test data specific to the target cell chemistry. Conversely, online techniques employ adaptive algorithms that update the cell model as it is being used. The novel method presented in this paper employs recurrent offline updates of the EEC parameterization set, and thus, it integrates the advantages of the offline approach, such as flexibility, reduced complexity, and improved run-time performance, with the main benefit of the online counterpart, which is the capacity to adapt the model parameterization to uncharacterized operating conditions. Based on an extensive set of experimental and simulation results obtained from tests specified in the IEC 62660-1 standard, it is shown that the proposed approach offers a significant accuracy improvement over simple offline methods, as well as enhanced runtime speed in comparison with commonly employed online strategies.

Feasibility of High-Frequency Alternating Current Power for Motor Auxiliary Loads in Vehicles

This paper presents a feasibility study into the application of a 100-V, 50-kHz high-frequency ac (HFAC) network for powering automotive electrical auxiliaries. The study is focused on motor-actuated loads and is divided into two sections. First, the investigation indicates the benefits of replacing low-torque dc motors with lighter and more efficient 400-Hz ac machines for applications such as electric fans, fuel pumps, or blower motors. A comparative examination of commercially available machines indicates space and weight reduction of more than 60%, and efficiency savings between 25% and 100% are possible. Second, the inquiry evaluates the viability of replacing existing dc/ac inverters with HFAC/ac converters for high-torque ac machines as employed, for example, in electric-power-assisted steering (EPAS) or heating, ventilation, and air conditioning systems. Based on experimental and simulation results for a column-assist EPAS application employing a three-phase permanent-magnet synchronous motor, this paper shows that an HFAC drive is expected to reduce the voltage harmonic content below 50 kHz by at least 10% compared with the dc/ac inverter. However, the disadvantages of the former drive make it less attractive than the existing dc/ac circuit. Specifically, the EPAS motor torque ripple is expected to be approximately 2% higher compared with the dc counterpart drive. Further drawbacks of the HFAC/ac drive include high metal-oxide-semiconductor field-effect transistor (MOSFET) conduction losses, higher voltage harmonics above 50 kHz, and complex control requirements of the inverter. Conclusively, significant HFAC advantages for motor loads can only be attributed to machines with a nominal torque capability that is limited to 2 N ·m. However, given the number of such devices within a typical vehicle, this translates into a possible vehicle mass saving of 30 kg and a potential reduction in fuel consumption by 0.8 L/100 km.

A methodology to determine drivetrain efficiency based on external environment

In this paper a statistical method for establishing the efficiency of the drivetrain under different real-world usage conditions has been proposed. The method is based on real-world driving data from an electric vehicle (EV) trial conducted in the UK. It was found that the external environment (road-type and traffic) causes distinct operating regions in the drivetrain. This paper makes use of a neural network to predict the road-type and introduces two new variables (start-stop index and congestion index) to establish the external environment. Based on this external environment a new metric called frequency weighted distribution is introduced to evaluate the performance of the drivetrain. This methodology of design based on the driving environment is of importance to newer advanced powertrains such as hybrids and EVs. The end result would be a design which caters to a specific usage profile.

Design of an optimized charge-blended energy management strategy for a plugin hybrid vehicle

This paper introduces the design of a charge blended energy management control system for use within a plugin hybrid electric vehicle. The approach taken extends the local cost function optimization routine associated with an Equivalent Fuel Consumption Method (EFCM) in which the charge-sustaining penalty factor is calculated online from an integrated PI controller rather than being derived from a pre-calibrated lookup table. The performance of the controller for a hybrid vehicle exercised over a number of different drive-cycles is presented. The powertrain model used to design and evaluate the system is derived from data logged onboard a number of different electric vehicles under real-world driving conditions.

A Novel Robust Predictive Control System Over Imperfect Networks

This paper aims to study on feedback control for a networked system with both uncertain delays and, packet dropouts and disturbances. Here, a so-called robust predictive control (RPC) approach is designed as follows: 1) delays and packet dropouts are accurately detected online by a network problem detector; 2) a so-called proportional-integral-based neural network grey model (PINNGM) is developed in a general form to be capable of forecasting accurately in advance the network problems and the effects of disturbances on the system performance; 3) using the PINNGM outputs, a small adaptive buffer (SAB) is optimally generated on the remote side to deal with the large delays and/or packet dropouts and, therefore, simplify the control design; 4) based on the PINNGM and SAB, an adaptive sampling-based integral state feedback controller is simply constructed to compensate the small delays and disturbances. Thus, the steady-state control performance is achieved with fast response, high adaptability, and robustness. Case studies are finally provided to evaluate the effectiveness of the proposed approach.

The control-oriented design and simulation of a high voltage bus management strategy for use within hybrid electric vehicles

A control-orientated model of the electrical architecture for a hybrid electric fuel cell sports vehicle is presented. Creating a control model is a critical first step in understanding the dynamic behaviour of the system and the subsequent design and verification of the control algorithms. The proposed control strategy is made up of both feedback and supervisory control elements. The high voltage bus management system is verified by means of incorporating the solution within a complete non-linear powertrain model of the vehicle. Simulation results are presented that show the performance of the vehicle for both high driver demand manoeuvres and conventional European and US legislative drive-cycles.

Defining Performance Metrics for Hybrid Electric Vehicles

The quantitative assessment and comparison of different hybrid vehicle options has traditionally been done on the basis of measuring or estimating the vehicles fuel economy over predefined drive-cycles. In general, little or no consideration has been given to the more subjective and difficult to quantify vehicle requirements, such as trying to understand which derivative will be the most “fun” vehicle to drive. A lack of understanding in this area of vehicle performance sufficiently early within the development life-cycle so as to be in a position to influence the vehicle design, can lead to a compromised powertrain architecture which will ultimately increase the risk of product failure.

Modelling the acceleration and braking characteristics of a fuel-cell electric sports vehicle equipped with an ultracapacitor

Abstract The traditional method of assessing the performance of a hybrid electric power-train is to construct a backward-facing model of the vehicle and then to exercise that model over a number of different legislative and ‘real-world’ drive cycles. Because of the low rates of acceleration and braking associated with such drive cycles, the effect of tyre dynamics on vehicle performance and powertrain efficiency, including that of regenerative braking, have been generally ignored in previous studies. Contained within this paper is the design of a detailed mathematical, physics-based model of a lightweight fuel-cell hybrid sports vehicle. The model is appropriate for studying the dynamic performance of the powertrain during periods of high acceleration and regenerative braking that are commensurate with the use of the vehicle as a sports car. The model characterizes both the electrical subsystems within the powertrain and the mechanical components including the longitudinal dynamics of the tyres. Simulation results show that, during rapid acceleration and braking, the effect of tyre losses on the performance and energy efficiency of the powertrain cannot be neglected. In addition, control objectives for the vehicle are also identified that aim to maximize the potential benefits associated with the integration of fuel-cell and ultracapacitor technology.

Powertrain modelling for engine stop-start dynamics and control of micro/mild hybrid construction machines

Engine stop–start control is considered as the key technology for micro/mild hybridisation of vehicles and machines. To utilise this concept, especially for construction machines, the engine is desired to be started in such a way that the operator discomfort can be minimised. To address this issue, this paper aims to develop a simple powertrain modelling approach for engine stop–start dynamic analysis and an advanced engine start control scheme newly applicable for micro/mild hybrid construction machines. First, a powertrain model of a generic construction machine is mathematically developed in a general form, which allows to investigate the transient responses of the system during the engine cranking process. Second, a simple parameterisation procedure with a minimum set of data required to characterise the dynamic model is presented. Third, a model-based adaptive controller is designed for the starter to crank the engine quickly and smoothly without the need of fuel injection while the critical problems of machine noise, vibration and harshness can be eliminated. Finally, the advantages and effectiveness of the proposed modelling and control approaches have been validated through numerical simulations. The results imply that with the limited data set for training, the developed model works better than a high fidelity model built in AMESim while the adaptive controller can guarantee the desired cranking performance.

Modelling the electric air conditioning system in a commercially available vehicle for energy management optimisation

Among the auxiliary systems on electric and hybrid electric vehicles the electric air conditioning (eAC) system causes the largest load on the high voltage battery and can significantly impact the energy efficiency and performance of the vehicle. New methods are being investigated for effective management of air conditioning loads through their integration into vehicle level energy management strategies. For this purpose, a fully integrated vehicle model is developed for a commercially available hybrid vehicle and used to develop energy management algorithms. In this paper, details of the eAC model of this vehicle are discussed, including steady state component validation against rig data. Also results of simulating the cabin pull-down are included.