What is in-vehicle data and why does it matter more for EVs? | Telematics data use cases for EV Charging
What is in-vehicle data and why does it matter?
Modern vehicles are not just mechanical wagons, they’re massive data centers on wheels. These vehicles are equipped with a range of sensors, ECUs (Electronic controller units) and analytical capabilities – that enable the collection of a so much data. They not only collect general vehicle/driving data such as fuel efficiency, tire pressure, engine performance and Environmental Factors such as Weather conditions and road quality., but also collect a lot of personal data such as Driving Style (Information on acceleration and braking patterns), Journey Details (Routes taken and GPS locations), Synced Smartphone Data (Contacts, music preferences, call logs from connected devices) and data related to car repairs and servicing.Why is in-vehicle telematics data more important for electric vehicles?
The range of electric vehicles varies a lot based on several factors (many of the data points mentioned above). Knowing these data will help to estimate the left range more accurately, assess a suitable charger/navigation, and also in case of failures, relevant debug mechanisms accordingly. Let’s take a deep dive into all these data - by broadly classifying them into electric vehicle-related, battery-related, and Plug&Charge contract-related data.
All these data are needed for EV charging infrastructure to create an optimal experience for the consumer and facilitate smart grid management.
All these data are needed for EV charging infrastructure to create an optimal experience for the consumer and facilitate smart grid management.
Battery-related in-vehicle telematics data & their use case scenario:
1. Battery size/capacity (max. usable energy of the EV battery) : Allows CPOs to calculate the range the consumer has in kilometers rather than % which is much more consumer friendly.
2. Battery temperature, incl. information on optimal battery temperature for charging (charge or discharge performance): Battery temperature is one of the parameters that has the most influence on charge speed. The number one consumer complaint when it comes to DC chargers is that their charging speed is lower than expected. In most cases, this is because their vehicle’s battery temperature is too low.
Having this information will allow CPOs to inform consumers correctly when the charging speed is lower than the respective vehicle type/model is capable of producing. It will also allow CPOs to indicate to the consumer or predict which element is limiting the charging power and calculate a reliable remaining charging time.
3. Current vehicle consumption (vehicle calculated, alt. prev. 100km, kWh/100km)/ Information on range per kWh : This is, in combination with other parameters, is needed to calculate the available range for the consumer in kilometers rather than in percentage of battery as kilometers are a better indicator for consumers of remaining range.
4. State of Charge (SoC): This exists for DC charging but not for AC. However, it can help to perform better energy management. It can contribute to:-Smart charging use cases-Flexibility services-Grid services It is the most crucial information for smart charging since it permits CPOs to shift consumption to times of low-carbon electricity being available or times without grid congestion.
5. Required energy till minimum, maximum & target SOC: For calculating and communicating to the consumer the time remaining for a charging session, based on consumer-defined inputs, to help plan how time is spent while charging; meanwhile, optimize for throughput (e.g. using timely push notifications informing on charge progression).
6. Recharged range: This would allow communication with the consumer about what additional range has been added to the battery during the current charging session.
7. EV charging status, fault/error communication (including issue information to increase transparency to the end consumer on status and ensure equal service level): Use issue information to increase transparency to the end consumer on status and ensure equal service level.
8. Possible and expected charging curve (charge point availability planning and load management): The charging curve is an important variable for the calculation of expected charging duration, which, in turn, improves predictions of charge point availability on the CPO side. Additionally, the expected charging duration should be displayed to the consumer.
9. Current charging power (charge speed): To communicate to the consumer at what speed the vehicle is currently being charged, which would give insight into expected charging time, battery performance and could signal a possible issue with the vehicle or charger in case the charging speed deviates from expected speed.
10. Capability for reverse power transfer: To assess if a vehicle is capable of bidirectional charging.
11. Time of departure: If the expected time of departure is specified by the consumer, it represents valuable information for CPOs and MSPs to optimize charging schedules based on grid congestion and electricity market signals.
Vehicle related in-vehicle telematics data & their use case scenario:
1. Vehicle type, model, build year: This is the most impactful data point for CPOs as it allows them and charger manufacturers to debug issues. Currently, CPOs and charger manufacturers ‘guess’ which vehicle is charging from a combination of factors that make it (a) difficult and (b) inaccurate. In case of bugs/errors, this information is key in debugging and solving the problem. Solving the problem means a better consumer experience.
Additionally, this will allow for a more customized experience for consumers, such as showing their vehicle picture on the charger screens, giving them accurate charging advice, and helping them better in case of errors (see first point above).
2. Stable vehicle identifier over the lifetime (in support of fraud detection and mitigation), e.g. VIN number, ISO 15118 EVCCidor MAC address: This has three use cases:
- (a) create/improve alternative payment methods to Plug & Charge (i.e. there is currently Autocharge, but with this parameter, it will become more secure and available to more vehicle models),
- (b) fight fraud and
- (c) allow CPOs to understand better consumer behaviors, which in turn will make for better pricing and offers to consumers. Of course, given that this is sensitive information (as a unique vehicle identifier), it must be treated as such and in compliance with GDPR.
3. Vehicle preconditioning status (alternatively, maximum power the battery can take at this moment vs. optimal situation and the reason for explaining the difference)/Vehicle preconditioning activation: See battery temperature: this explains why the charging speed is lower than expected if the vehicle battery is at fault. It can also help CPOs suggest to the consumer to activate the preconditioning of the battery in case it is not on. Provides the ability to activate this remotely, e.g. from a third-party charging app in the vehicle so that the consumer benefits from faster charging while increasing charging pool throughput.
4. Vehicle geolocation (improved charging experience within charging parks): Helps consumers navigate to an available charging spot within or in proximity to a charging pool. Additionally, combined with vector, this allows for recommending chargers nearby.
5. Vehicle climate control/air conditioning status: To factor in this impact on SoC for providing relevant charge stop recommendations.
6. Access to onboard navigation function (provide charge-stop recommendations): Knowing where the consumer is heading and the current SoC allows for providing smart charge-stop recommendations en route.
7. Inlet/port number and location (back, front, side): Useful for automated charging and autonomous EVs in the future.
8. Vehicle preconditioning status (alternatively, maximum power the battery can take at this moment vs. optimal situation and the reason for explaining the difference): For explaining how to reach maximum charge speed to the consumer (addressing main consumer feedback) and how this is affected by (not) having preconditioning enabled.
Plug&Charge related in-vehicle telematics data & their use case scenario:
1. Vehicle Plug & Charge capability: To inform consumers about Plug & Charge (in the future) if they don’t have it activated yet (which is in everybody’s interest since it will speed up the charging process and likely increase the charging success rate since authentication should (almost) never fail).
2. Installation status of Plug & Charge contract: If the CPO would have to facilitate certificate installation through the charger, over ISO15118, knowing the installation status (and possible installation errors) will help inform the consumer on how this is proceeding and complete successfully.
3. Installed & currently activated Plug & Charge contract (consumer information on charging error): In the light of providing full pricing transparency, inform consumers what they will pay per kWh for these contracts at this charger so that they can choose the preferred contract for this charging session.
Who owns this data?
Today’s legislation grants car manufacturers unrestricted access to vehicle-generated data, allowing them the discretion to withhold such information from third-party service providers. Currently, in-vehicle data are controlled and exploited commercially by vehicle manufacturers (OEM). Other market participants, such as automotive suppliers, but also independent repair shops, insurance companies, parking space providers etc. depend on OEMs to make data available.Such preferential treatment of access to in-vehicle data distorts competition and prevents the EV charging sector from providing the most optimized charging experience. This further restricts consumers' choice in selecting services.
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