Maximum efficiency for minimum costs of electric car charging

Transcription

1 Maximum efficiency for minimum costs of electric car charging How to optimize the performance of your electric cars and charging stations in order to make them really cost-effective and attractive for your customers CalBatt S.r.l. Technest, P.zza Vermicelli, Rende, CS Ph

2 Summary Introduction... 3 Charging efficiency and costs: business cases... 3 Charging time matters, but it is not everything... 5 CalBatt goal: the best trade-off between charging time and efficiency... 7 Conclusions... 9 References... 9 About CalBatt This white paper analyzes how the charging efficiency of electric cars can significantly impact on both the operating costs for electric cars owners and the profitability of public charging stations for service providers. It is also discussed how the actual electric car charging efficiency can be significantly lower than the peak efficiency potentially achievable by the system in common real situations in which charging processes are not optimally controlled, making efforts spent by charging systems manufacturers in designing both high-performance chargers and batteries less profitable than expected for their customers. This remarkable problem can be solved by embedding into the system smart charge controllers, which allow implementing ad-hoc charging strategies to guarantee always the best trade-off between charging time and efficiency according to specific user needs. As shown by experimental tests carried out by CalBatt together with the Engineering and Research Division of Enel S.p.a on different battery technologies, these smart charge controllers can allow a charge efficiency increase of up to 15%, resulting in a significant reduction of recharge costs. 2

3 Introduction A fraction of the energy bought to recharge the car is actually dissipated as heat because of charging inefficiencies Among all the benefits of electric cars compared to traditional gasoline ones, the lower fuel cost appears as one of the most important drivers to promote the widespread adoption of electric transportation. In fact, depending on both gasoline and electricity costs, electric car recharging can be significantly cheaper than gasoline car re-fueling. For example, driving an electric vehicle costs on average about three times less in US [1]. In this scenario, it is important to realize that a fraction of the energy bought to recharge the car is actually dissipated as heat because of charging inefficiencies, leading to a hidden economical loss for both car owners and charging stations service providers. Thus, along with the cost reduction of car battery packs and the creation of an adequate fast charging infrastructure, the optimization of charging efficiency appears as one of the success factors to make the investment actually viable for electric cars owners and charging stations service providers. This fundamental aspect will be discussed in detail in the next section by means of some practical examples. Charging efficiency and costs: business cases In the following, an analysis of the costs for electric car recharging is carried out for two different scenarios: Scenario 1: Public charging stations with pay-as-you-go tariff. Scenario 2: Public charging stations with flat tariff. Fig. 1 summarizes all the assumptions of the analysis about number of subscribed users, number of public recharges for each user, typical electric car charging tariffs for the user and electricity tariffs for the service provider in Italy [3]. The examples discussed in the following refer to the comparison, in terms of costs for electric car charging, between two different cases: Case 1. In this case, the charging efficiency is assumed to be 80%. Case 2. In this case, the charging efficiency is assumed to be 92%, under the hypothesis of achieving, for example, a 15% relative increase of the efficiency by optimizing the performance of the charging system of the case 1. Fig. 2 shows the results of the analysis for the two scenarios considered. It appears that in the case of pay-as-you-go tariffs, the higher charging efficiency of case 2 leads to a cost saving for the user 40 /year, thus with a 13% cost reduction. Obviously, in the case of flat tariff, the user does not benefit of any charging efficiency improvements, but the higher efficiency of case 2 allows the service provider to 3

4 complete the charging processes by buying less energy from the grid. This results in a profit for the service provider of 1250 /year per charging station, thus with a 12% profitability increase. Scenario 1 (pay-as-you-go): assumptions Scenario 2 (flat): assumptions Fig. 1. Assumptions of the analysis for the different scenarios considered Scenario 1 (pay-as-you-go): Analysis of costs Scenario 2 (flat): Analysis of costs Fig. 2. Analysis of costs for electric car charging for the different scenarios considered 4

5 Obviously, similar considerations can be also extended straightforwardly to home charging and to other cases characterized by different tariffs. In summary, the presented analysis clearly highlights that, together with the cost reduction for car battery packs and the creation of an adequate fast charging infrastructure, suppliers of electric cars and charging stations have to cope with the 3 maximization of charging efficiency to improve the quality of service for their customers. The next section will focus on strategies to achieve the charging efficiency maximization. Charging time matters, but it is not everything Together with the cost reduction for car battery packs and the creation of an adequate fast charging infrastructure, suppliers of electric cars and charging stations have to cope with the maximization of charging efficiency to improve the quality of service for their customers It is indubitable that the first step towards the charging efficiency optimization is to design both the battery and the charger so to try maximizing the peak charging efficiency of the system. However, peak charging efficiency is just a measure of the maximum performance achievable by the system when the battery and the charger operate in their optimal working regions. In real situations, the system components may operate indeed far from their optimal working regions during charging processes, leading to a real operational efficiency of the system significantly lower than its peak efficiency. This is what commonly occurs in typical practical cases in which charging is performed taking into account just charging time constraints, without considering if the resulting selected profile of the charging power makes the battery and the charger to operate at their maximum efficiency or not. The variations of charging efficiency with the charging profile selected (and thus on the charging time resulting from the profile chosen) is actually an issue that the most discerning users are already experiencing in real life, as highlighted by numerous threads in electric car user forums, such as that of Tesla [2]. From the topics arisen, it appears in fact that several users are asking some decisional tool to help them in understanding which is the real cost of recharging their car and how it depends on the charging settings set. In some cases people try also to give simple rules of thumbs to maximize the charging efficiency, sometimes suggesting to charge as faster as possible, sometimes to charge instead as slower as possible. However, the truth is that unfortunately there is not some kind of golden rule to select a-priori an optimal charging profile which is good every day for each car, because it depends on: 5

6 Charging efficiency the characteristics of the particular charger and battery, which are in general affected also from aging and from their previous history; parameters which change continuously with the battery state of charge. This generally makes the charging efficiency to depend in a complex non-monotonic way by the charging time, as shown by the conceptual example of Fig. 3. The plot in the figure reports a possible realistic dependence of the actual charging efficiency on the charging time for a system whose battery and charger are respectively characterized by a maximum efficiency of 97% and 95%, resulting in an peak efficiency of 92%. If charging is not carried out very carefully, the real charging efficiency will be unavoidably lower than the peak efficiency achievable, except in the case of fortuitous conditions in which the charging setting set are just casually the right ones that make the charger and the battery to be operated in their optimal working regions in that specific moment. In the plot, this is pictorially reported as occurring by setting a charging profile leading to a charging time of 30 minutes just as an example, but generally it can occur for different charging profiles (and thus charging times) depending on several factors. 0,94 After highperformance devices have been built, it is thus crucial to be capable of optimizing actually the charging performance on the field in order to increase customer satisfaction 0,92 0,9 0,88 0,86 0,84 0,82 0,8 0, Charging time (min) Fig. 3. Conceptual example of the trend of the charging efficiency as a function of the time required to complete the charging process Obviously, the possible energy losses arising from the problem discussed above, can make the efforts of electric cars and charging stations manufacturers in optimizing the design of both the charger and the battery less fruitful than expected in terms of cost saving for the end user. 6

7 After high-performance devices have been built, it is thus crucial to be capable of equipping the charging system with some tool capable of optimizing actually the charging performance on the field in order to increase customer satisfaction. This goal can be achieved only by setting optimal charging profiles allowing to achieve always the best trade-off between the charging time and efficiency according to specific user needs. To this aim, common tools such as existing energy meters are practically useless, because they do not give a clear vision of how optimizing in a systematic way each car recharge. Thus, the implementation of an electric car charging system targeted to be really appealing for the end-user further requires the essential presence of a new kind of smart charge controllers capable of realizing ad-hoc optimal charging strategies. CalBatt goal: the best trade-off between charging time and efficiency CalBatt has answered to the urgent need of smart dynamic charging optimizers by developing innovative solutions based on a proprietary patented technology which allows, for each particular electric car charging system, to: CalBatt solutions provide the still missing link to bring together the efforts in developing highperformance electronic power converters, batteries and smart vehicle energy management systems accurately predict the charging time and efficiency under every likely operating condition; plan the most convenient charging profile in order always to achieve the best trade-off between the charging time and efficiency according to specific user needs; maximize the charging efficiency by optimizing in real time the charging profile. CalBatt technology is implemented by NomoStor, an electronic expansion card offered to charging system manufacturers, customizable on demand to be integrated both in on-board chargers to optimize the charging of a single vehicle (Fig. 4a) and in charging stations, in order to make them really able to perform an optimal and efficient electric vehicle fleet management (Fig. 4b). 7

8 Battery pack Charger (a) Smart fleet manager Control (b) Fig. 4. Use of CalBatt NomoStor into: a) on-board chargers; b) charging stations To demonstrate the effectiveness of the developed technology, experimental tests have been carried out by CalBatt together with the Engineering and Research Division of Enel S.p.a. In these tests, CalBatt solutions have been used to maximize the operational efficiency of the charging process of different systems, which have been implemented by using the same commercial charger with different battery technologies, among which Lithium Ion typically used in electric cars. 8

9 As highlighted by experimental results, the optimal management strategy guaranteed by CalBatt solutions can lead to a charging efficiency improvement of up to 15%. This improvement results in a significant amount of energy saved for the electric car owner or the service provider. In fact, according to the analysis previously shown, the measured 15% efficiency increase achieved by adding CalBatt solutions to the electric car charging system can guarantee: a cost reduction of up to 13% for the car owner in the presence of pay-as-yougo tariffs; a profitability increase of up to 12% for the service provider in the presence of flat tariffs; thus taking a decisive step forward in making the investment in electric cars and charging stations more attractive for users. Conclusions Electric car charging systems embedding CalBatt solutions can allow the unique possibility of achieving for each recharge the most convenient tradeoff between charging time and efficiency according to user needs The recharge costs of electric cars are significantly affected by the charging efficiency. For this reason, together with the battery cost reduction and the creation of an adequate fast charging infrastructure, charging system manufacturers should have to cope with the efficiency maximization very carefully in order to increase the appeal of electric cars and charging stations for users. To this aim, other than optimizing the design of both the charging system and the battery, it is fundamental to equip the system with a smart charging optimizer capable of guaranteeing always optimally tailored charging profiles. According to experimental tests carried out by CalBatt together with the Engineering and Research Division of Enel S.p.a, the CalBatt method can guarantee an operational efficiency increase of up to 15% during battery charging processes. Thanks to these unique features, electric car charging systems embedding CalBatt solutions can allow the unique possibility of achieving for each recharge the most convenient trade-off between charging time and efficiency according to user needs. References [1] The egallon: How Much Cheaper Is It to Drive on Electricity?, [2] Tesla forum, [3] Italian electric car charging tariffs, 9

10 About CalBatt Calbatt is a spin-off company of the University of Calabria-Italy. The Company was founded in 2011 to valorize the know-how and the intellectual property developed in the continual and internationally recognized academic research activity of the founders in the field of electronic systems. In 2011, CalBatt was selected as the best business idea in the Techgarage competition, and has been one of the finalists of the Italian Innovation Award. In 2013, CalBatt was an award winner in the Enel Lab competition. In 2014, CalBatt was ranked in the top 10 most interesting innovative Tech-Ventures at the Munich Cleantech Innovation Award and won the "Best Presentation Award" at the Cleantech Summit in Rotterdam. Thanks to its patented pioneering technology for the dynamical analysis and performance optimization of storage systems, CalBatt offers to its partners an innovative complementary tool to boost the efficiency of their storage or electric car charging systems. Experimental tests carried out together with the Engineering and Research Division of Enel by using commercially available battery chemistries have demonstrated that CalBatt technology can allow an efficiency increase of up to 15%. To find out how much your business can benefit from using CalBatt solutions, contact us at or visit: CalBatt is a registered trademark of CalBatt Srl. All other registered trademarks or trademarks are property of their respective owners. 10