Jonas Hellgren

Maximisation of brake energy regeneration in a hybrid electric parallel car

This paper deals with the effective brake energy regeneration of parallel hybrid electric vehicles. A computational procedure to maximise the regenerated brake energy during braking is presented. Mathematical modelling, optimisation and computer simulation are essential tools. In addition to the computational procedure, an extensive sensitivity analysis is carried out on a medium-size car. The relation between the regenerated brake energy and the following properties are surveyed: rear and front electric machine efficiency; vehicle stability restriction; ICE drag torque; brake system characteristic; battery power; transmission ratios and battery resistance. Two driving cycles are evaluated: SFTP SC03 includes more aggressive decelerations than the other cycle, NEDC. By switching between front-wheel and all-wheel drive and changing clutch arrangements, four different powertrain configurations are derived. All previously presented properties are analysed for each driving cycle and powertrain configuration. The results show, for example, that electric all-wheel drives tend to regenerate more brake energy compared with front-wheel drives in aggressive driving cycles.

Including a Battery State of Health model in the HEV component sizing and optimal control problem

This paper studies convex optimization and modelling for component sizing and optimal energy management control of hybrid electric vehicles. The novelty in the paper is the modeling steps required to include a battery wear model into the convex optimization problem. The convex modeling steps are described for the example of battery sizing and simultaneous optimal control of a series hybrid electric bus driving along a perfectly known bus line. Using the proposed convex optimization method and battery wear model, the city bus example is used to study a relevant question: is it better to choose one large battery that is sized to survive the entire lifespan of the bus, or is it beneficial with several smaller replaceable batteries which could be operated at higher c-rates?

Convex optimization of charging infrastructure design and component sizing of a plug-in series HEV powertrain

With the topic of plug-in HEV city buses, this paper studies the highly coupled optimization problem of finding the most cost efficient compromise between investing in onboard electric powertrain components and installing a charging infrastructure along the bus line. The paper describes how convex optimization can be used to find the optimal battery sizing for a series HEV with fixed engine and generator unit and a fixed charging infrastructure along the bus line. The novelty of the proposed optimization approach is that both the battery sizing and the energy management strategy are optimized simultaneously by solving a convex problem. In the optimization approach the power haracteristics of the engine-generator unit are approximated by a convex, second order polynomial, and the convex battery model assumes quadratic losses. The paper also presents an example for a specific bus line, showing the dependence between the optimal battery sizing and the number of charging stations on the bus line.

A Systematic Way of Choosing Driveline Configuration and Sizing Components in Hybrid Vehicles

Energy saving in general and less polluting vehicles in specific, become more and more urgent topics. One reason is that, in a world where the demand for fast transportation is increasing, the risk of global warming is a fact. Hybrid Vehicles (HV:s) are proposed as a more environmentally friendly candidate than conventional vehicles. Nowadays, there are numerous different types of HV:s and the components can, in theory, be sized in infinite ways. There is no simple answer to how to choose driveline configuration and size components in a HV. This paper describes one method, Driveline Synthesis (DS), that systematically presents a suitable driveline, on the basis of demands and conditions. Examples of demands are driving cycle and emission free zones. Some conditions are fuel price, tax on pollution and discount rate. The most suitable driveline is defined as the most cost effective. Total cost is defined as the sum of: cost of components, fuel cost, cost of external energy and cost of pollution. Genetic algorithms are used as an optimization method. Two major types of drivelines are compared in a case study, a conventional bus with a diesel engine and automatic transmission versus a series hybrid bus with different types of primary power units (diesel engine or fuel cell) and storage devices (super capacitor or NiMH battery). DS gives reasonable answers but needs further validation and development. One conclusion from the work is that the most suitable driveline configuration depends very much on demands, conditions and present technology, i.e. HV:s are only preferable to conventional vehicles under special circumstances.

Optimization based design of heterogeneous truck fleet and electric propulsion

Many researches have been focused on vehicle routing problem during past decades where subject vehicles are previously fully designed and ready to start operation. Further, extensive studies have been done on powertrain design irrespective of the routes where the vehicle is going to be employed. In the present paper, we try to define a new branch of problems where the vehicle design, in particular its propulsion system and loading capacity, is treated simultaneously with the routing problem. The focus is on optimization based design of heterogeneous electric truck fleet to perform a prescribed task with a lowest cost on an available set of routes. The approach is illustrated in a simple case study problem. It is shown that long heavy combination vehicles are energy-efficient but not cost-optimal on short routes.

Feasibility of Electrifying Urban Goods Distribution Trucks

This paper discusses the feasibility of electrifying medium to heavy urban goods distribution trucks. As a case study, an existing transport system in the Swedish city of Gothenburg is used. The project is a joint research effort between a vehicle OEM, an electric utility, a fleet operator, the Swedish Transport Administration and two research organizations. One main objective is to determine if and when different electrified powertrains are cost efficient to the end user. The results indicate that by 2015 conventional powertrains are still probably the most cost effective alternative in all applications studied. But in 2025, electrified powertrains are most cost efficient for most transport scenarios. These results indicate a transition in preferred powertrain technology for urban trucks within the coming ten years. It is important to point out that this result may not be general. Driving patterns, energy price developments and technology maturity of components such as batteries and motors greatly influence the total cost of ownership and large regional differences in when such a transition may occur are expected. In addition to the total cost of ownership, important issues for a successful deployment are policies (e.g. restricting access to urban areas for noisy and polluting vehicles), information and communication solutions (e.g. adapted route planning), access to a cost effective charging infrastructure (and low-carbon electricity production) and new business models. These must all be developed in parallel to the vehicle and powertrain technology. The large number of different stakeholders involved in this transition is also a challenge in itself.

Energy storage system optimisation of a plug-in HEV

This paper deals with the optimisation of the energy storage system of a parallel hybrid plug-in car. The objective is to study how the electric driving range is influenced by factors such as package volume and auxiliary power consumption. Simulation and optimisation are used to find the most cost effective battery arrangement for specified electric driving range, volume, power and lifetime requirements. Two battery technologies, NiMH and Li-ion, are included in the simplified case study. The result indicates that the battery cost and size are highly dependent on the required electric driving range. It is found that a 3±5km electric driving range is possible with a minor cost increase. An electric driving range of 15±25km is possible, but results in a more bulky, and much more costly, battery system. It is important to point out that the results are not general. The electric driving range can be significantly extended by decreasing the roll and/or the air resistance.

Sensitivity analysis of optimal energy management in plug-in hybrid heavy vehicles

Optimal energy management strategies of hybrid vehicles are computationally expensive when considering the entire trip ahead rather than a short upcoming horizon. Considering the entire representative trip is already needed in concept design stages of the vehicle. In order to come up with an appropriate design while minimizing the total ownership cost the energy management strategies must already be used together with early concept evaluations. To investigate the possibility of replacing the optimal energy management with simpler approaches, here, the sensitivity of optimal solution to some of vehicle parameters and traffic flow is studied. It is seen that a simpler approach, i.e. an instantaneous optimization, can be used, in case of smooth traffic flow, since the gain of optimal strategy in reduction of operational cost is less than 4% for different vehicle hardware setup and for selected representative driving cycle. Dynamic programming is used as a solution method for finding the optimal strategy.

Tool for Energy Storage System Synthesis

An essential part of Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) is the Energy Storage System (ESS). This paper describes a tool, named Tool for Energy Storage System Synthesis (TESSS), that automatically transforms ESS demands to cost-effective ESS design candidates. The following statements characterise the tool: 1) mathematical modelling and optimisation are essential ingredients; the handled ESS technologies are batteries of various types, supercapacitors and combined ESSs. Combined ESSs include both battery and supercapacitor cells. 2) the optimal design is pointed out by a cost function and requirements. The cost function includes investment cost, wear cost and costs due to energy losses. Examples of requirements are minimal power, maximum package volume and voltage. 3) TESSS is user friendly and extremely computation efficient owing to its compiled C code. To exemplify the practical use of the tool, two case studies are also presented in this paper.